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Founding AI Scientist - Pathology Foundation Models Remote (Must be US Based) The Role You will lead the strategy and development of pathology foundation models, shaping how they are designed, trained, evaluated, and deployed into clinical and pharmaceutical applications. This is a highly cross-functional role spanning research and production. You will define how foundation models integrate with biological context, multimodal data, and downstream decision-making systems moving beyond isolated model improvements to building end-to-end, real-world solutions. As an early-stage hire, you will play a key role in shaping both the technical direction and the organisation itself. Required Experience • Strong publication record in machine learning, including multiple first-author papers at leading conferences or journals, • Deep understanding of modern ML architectures (e.g. transformers, attention mechanisms, state-space models, mixture-of-experts), • Experience working with GPU clusters and large-scale ML infrastructure (e.g. Kubernetes, SLURM, or similar), • Solid software engineering skills and ability to build production-grade systems, • Excellent communication skills, with the ability to convey complex ideas to both technical and scientific audiences Preferred Background • Experience in oncology, cancer biology, or drug development, • Exposure to biomedical or healthcare foundation models, • Experience with multimodal and cross-modal learning systems, • Familiarity with healthcare regulatory frameworks (e.g. FDA, HIPAA), • Contributions to open-source ML ecosystems, • Experience working with distributed or community-driven research groups, • Previous experience in a startup or early-stage environment To apply please reach out to Sam Shinner at Discover International

You’ll join our Data team, report to our Head of Data, and help shape how data science is used across the company. Skool is hiring its first ever Data Scientist. Own data science work across growth, product, and user engagement, from analysis through measured results.

Drug Discovery Scientist Position: Drug Discovery Scientist Type: Hourly Contract Compensation: $60–$90/hour Location: Remote About the Opportunity This opportunity is for experienced Drug Discovery Scientists to contribute to an advanced AI research and evaluation project focused on pharmaceutical research and development. You'll apply your scientific expertise to design realistic, evidence-driven drug discovery problems that require AI models to reason through incomplete, indirect, and potentially misleading scientific evidence. You'll create research prompts, build supporting data rooms using real source-grounded information, develop rigorous grading frameworks, and validate the resulting tasks. The role is ideal for experts who can distinguish genuine scientific reasoning from pattern matching and confidently evaluate the quality of complex research conclusions. Responsibilities • Design challenging, realistic drug discovery research problems based on authentic scientific workflows., • Develop research scenarios where the correct conclusion must be derived from multiple pieces of evidence rather than directly stated., • Build comprehensive data rooms using real, source-grounded scientific data and documentation., • Ensure every decisive scientific value and piece of evidence can be traced back to a reliable source., • Create detailed grading documents and evaluation rubrics that assess scientific reasoning and substantive conclusions., • Evaluate AI-generated research outputs for scientific accuracy, logical consistency, and defensibility., • Run verification and calibration processes to ensure tasks are reproducible, appropriately difficult, and objectively scorable., • Identify weaknesses in task design, evidence, or evaluation criteria and revise them accordingly., • Provide expert judgment on scientific questions, task difficulty, and the quality of AI reasoning., • Collaborate with project reviewers and other domain experts to refine research tasks. Required Qualifications • Professional expertise in one or more of the following areas:, • Mechanistic enzymology, • Structure-guided peptide design, • Structure-guided antibody design, • Fragment-based drug discovery, • Structure-based medicinal chemistry, • PhD or equivalent industry experience in drug discovery, medicinal chemistry, chemical biology, biochemistry, or a closely related field., • Strong understanding of drug discovery research methodologies and scientific evidence evaluation., • Ability to construct complex scientific problems with defensible conclusions., • Strong analytical and critical-thinking skills., • Ability to evaluate scientific reasoning quality, not simply final answers., • Strong scientific writing and documentation skills., • Comfortable working independently in a remote research environment., • Ability to commit at least 20 hours per week. Preferred Qualifications • Experience designing or evaluating drug discovery research strategies., • Strong background in structure-based drug design, protein–ligand interactions, enzymology, or molecular discovery., • Experience working with scientific literature, experimental datasets, structural data, and research documentation., • Experience developing research assessments, scientific benchmarks, or evaluation frameworks., • Familiarity with open-source scientific tooling and computational research workflows., • Experience evaluating AI-generated scientific research or technical outputs is a plus., • Strong ability to distinguish defensible scientific conclusions from unsupported assumptions or superficial reasoning. Compensation • Competitive compensation of $60–$90/hour., • Hourly contract engagement., • Fully remote., • Minimum commitment: 20 hours/week., • Up to 40 hours/week available., • Claude Max subscription required for the project and fully reimbursed., • Work conducted through a browser-based research studio and Claude Code. Application Process • Apply to the role, • Complete the required screening questions, • Provide details about your drug discovery and scientific research experience, • Complete the relevant scientific assessment, • Participate in the evaluation/interview stage, • Complete onboarding and tooling setup, • Begin designing and evaluating drug discovery research tasks

Scope: We are hiring a pioneering, fully autonomous Lead Data Scientist to own the complete data science lifecycle for our flagship prediction model project. This role is mission-critical — the candidate will be the single point of expertise responsible for sourcing, analyzing, and engineering all data that powers our predictive models. Operating independently with minimal supervision, this individual must combine deep AI/ML mastery, hands-on engineering skills, and sharp business acumen to deliver measurable, production-grade outcomes. Key Responsibilities: Data Analysis & Pipeline Ownership ▸ Lead end-to-end analysis of large, complex, multi-source datasets to surface patterns driving model inputs ▸ Identify, collect, clean, validate, and transform all data required for prediction model consumption ▸ Design and maintain scalable, production-grade data pipelines (training, validation, inference) ▸ Perform deep EDA, data profiling, and quality audits to ensure model-ready data standards Predictive Modeling & AI/ML ▸ Architect, train, evaluate, and iterate ML models — supervised, unsupervised, and reinforcement learning ▸ Own feature engineering: selection, extraction, transformation, and dimensionality reduction ▸ Apply advanced techniques: deep learning, NLP, time-series forecasting, ensemble methods ▸ Benchmark, A/B test, and monitor models in production; drive continuous performance improvement ▸ Deploy models via REST APIs (FastAPI/Flask); ensure reproducibility and scalability Independent Ownership & Leadership ▸ Self-direct from problem definition through solution delivery with zero hand-holding ▸ Translate ambiguous business problems into precise, executable data science problem statements ▸ Communicate model results and data insights clearly to technical and non-technical stakeholders ▸ Document all experiments, methodologies, and outcomes — audit-ready and reproducible ▸ Champion best practices across the data science lifecycle; mentor junior team members QUALIFICATIONS ▸ B.S./M.S./Ph.D. in Computer Science, Statistics, Mathematics, or equivalent quantitative field (Master's/Ph.D. strongly preferred) ▸ 5+ years of hands-on data science experience with at least 2 years delivering production-grade ML models ▸ Proven ability to own and deliver end-to-end data science projects independently ▸ Portfolio demonstrating innovation in predictive modeling and measurable business impact ▸ Experience in a fast-paced, data-driven, decision-model environment REQUIRED SKILLS & QUALIFICATIONS Core Data Science & Mathematics ▸ Statistics (Bayesian inference, hypothesis testing, regression, distributions) ▸ Linear algebra, calculus, and probability applied to ML model design ▸ Supervised & unsupervised learning, anomaly detection, clustering ▸ Time-series analysis & forecasting: ARIMA, Prophet, LSTM Programming & Development ▸ Python (Expert): NumPy, Pandas, Scikit-learn, Statsmodels, Matplotlib, Plotly ▸ SQL (Advanced): window functions, CTEs, query optimization ▸ Git / GitHub; CI/CD for ML; MLOps with MLflow or Kubeflow ▸ Docker & Kubernetes for model containerization and serving AI / ML Frameworks (Must-Have) ▸ TensorFlow and/or PyTorch — deep learning architectures ▸ XGBoost, LightGBM, CatBoost — gradient boosting & ensemble methods ▸ Hugging Face Transformers — NLP, LLMs, and fine-tuning ▸ SHAP, LIME — model explainability and interpretability ▸ LLMs / Generative AI / Prompt Engineering — strong advantage Cloud & Data Infrastructure ▸ AWS (SageMaker, S3, Glue), GCP (Vertex AI, BigQuery), or Azure ML ▸ Apache Spark / PySpark — distributed data processing ▸ Airflow / Prefect — pipeline orchestration Snowflake (Good to Have) ▸ Snowflake Data Cloud: querying, Snowpark for Python ML pipelines ▸ Snowflake Cortex AI / ML Functions for in-database ML ▸ dbt for data transformation; data governance within Snowflake

This is a remote US role with a slight preference for candidates based in San Francisco, San Diego, or Boston. And 3+ years of industry experience in machine learning and data science. Strong domain knowledge in Women's Health and experience with health data from wearables are significant plusses.

We are looking for a Staff Data Scientist to join our Safety Insights Data Science team.

As an AI Engineering team member, you will have the opportunity to leverage cutting-edge data science, machine learning and AI on petabytes of data in ways that make a large and lasting impact on the company. You will collaborate closely with data analysts, account managers, product teams and engine

People Analytics & Research is a strong team of Data Scientists, Data Engineers, and Analysts. Experience applying data science to compensation, recruiting, or broader workforce and organizational questions, including work with legally sensitive data. We need a Data Scientist with a proven track rec

Leadership in data science: experience leading cross-functional teams of data scientists, data engineers, and data or cost analysts, and defining a data strategy aligned to organizational goals. Knowledge and experience performing cost estimating and analysis on major defense systems, including typi

Shopmonkey has the structured data and workflows to support serious data science work, and you'll have the rare opportunity to help build the analytical and ML foundation from the ground up, shaping how data-driven decision making scales alongside a maturing platform and defining what the future of

As an AI Engineering team member, you will have the opportunity to leverage cutting-edge data science, machine learning and AI on petabytes of data in ways that make a large and lasting impact on the company. You will collaborate closely with data analysts, account managers, product teams and engine

Working closely with Marketing, Product, Finance, and Technology, the Senior Data Scientist transforms complex data into actionable insights that improve business performance in a highly competitive telecommunications environment. The Senior Data Scientist, Advanced Analytics, develops machine learn

Our On-Demand Talent Solutions team is excited to announce an opportunity for a Senior Clinical Development Scientist to join our medical device client, whose primary focus is innovating artificial fibrillation and developing next generation cardiac ablation systems. Summary: This individual will play a key role in shaping clinical strategy, designing and executing global clinical studies, analyzing clinical data, and partnering cross-functionally with R&D, Regulatory Affairs, Clinical Operations, Marketing, and Key Opinion Leaders to advance the company's next generation of products. Responsibilities: • Lead the design, initiation, execution, and oversight of pre-market and post-market clinical trials, including pivotal studies for next-generation cardiac ablation technologies., • Develop and execute clinical strategy, clinical development plans, and EU MDR clinical evaluations supporting cardiac ablation catheters and PFA generators., • Oversee clinical data analysis to generate robust scientific evidence and meaningful clinical insights while supporting health economics and outcomes research initiatives., • Serve as the internal scientific expert in cardiac electrophysiology, atrial fibrillation, and cardiac ablation technologies, providing clinical input into product development documentation, IFUs, and technical materials., • Partner with Key Opinion Leaders (KOLs), clinical investigators, and physician advisors while representing the company at scientific conferences, advisory boards, and industry meetings., • Drive publication strategy, scientific communications, physician education, and product adoption through the interpretation and communication of clinical data. Qualifications: • MS, PhD, MD, or equivalent in Life Sciences, Medicine, Biomedical Engineering, or related field., • 3+ years of Clinical Development experience within medical devices., • Experience with Class III cardiovascular., • Cross-functional experience partnering with R&D and Regulatory Affairs., • Experience with clinical data analysis tools (MATLAB, Python, SAS, Minitab).

Data Scientist (Live Anywhere). Perform Exploratory Data Analysis (EDA). Proven track record of deploying models and data pipelines in cloud environments, preferably on GCP or other cloud platforms.

Data Scientist | AI & Machine Learning. Data Scientist | AI & Machine Learning. Position: Data Scientist | AI & ML Analyst.

About SaxeCap: SaxeCap is the premier AI transformation and investment platform in private equity. We created the concept of buying out traditional businesses and transforming them with AI in 2018, and today we are the go-to AI transformation partner for 60+ PE firms globally, including 9 of the top 10 by AUM and the world's leading sovereign wealth funds. We've transformed 140+ businesses across healthcare services, business services, financial services, software, consumer, and more, driving billions of dollars of enterprise value expansion along the way. We operate at the intersection of three businesses: a private equity investment arm, an in-house AI transformation firm that designs and deploys bespoke GenAI, ML, and automation solutions, and a suite of proprietary software products. Our team comes from places like Google, Palantir, Meta, Surge AI, Blackstone, TPG, Cerberus, Millenium, Balyasny, McKinsey, Bain, Oliver Wyman, MIT, Stanford, GSB, HBS, and Wharton. Our leadership includes early investors in OpenAI, Anthropic, Groq, SpaceX, Neuralink, Mercor, Lambda Labs, etc. But what makes our team exceptional isn't where they came from or what they've invested in, it's what they ship. We are builders, not slide-makers. About the Role: We are hiring a Forward Deployed AI Engineer to join our AI transformation team. This is not a typical software engineering role. You will not be maintaining a single codebase or optimizing one product. You will be building and deploying AI solutions across dozens of companies, industries, and problem domains, working directly with clients and PE sponsors to solve their highest-value business problems with production-grade GenAI, ML, and automation. In a given month, you might build a RAG system that automates a core operational workflow for a healthcare services company, deploy an ML model that optimizes pricing for a financial services platform, architect a data pipeline that unlocks analytics capabilities for a business that has never had them, and mentor junior engineers on the team through all of it. Every solution you build is tied to measurable business impact. You will see your code move EBITDA, not just pass tests. This role sits at the intersection of engineering excellence and client impact. You will be in the room with executives and PE partners, translating business problems into technical architectures, then building and shipping the solutions yourself. If you want to be the best AI engineer in the world, there is no faster way to get reps across industries, problem types, and AI techniques than this role. About You: You are an engineer who builds fast, ships to production, and cares about business outcomes, not just technical elegance. You are comfortable working directly with non-technical stakeholders, translating ambiguous business problems into clean technical solutions, and iterating in tight cycles. You take pride in code that works in the real world, not just in a notebook. Specifically: • 3+ years of experience building and deploying software products end to end (design, implementation, testing, deployment, maintenance), • Expert in Python (Django, Flask, FastAPI, Pandas, etc.) and/or JavaScript (React, Node). These are our primary languages and you should be deeply fluent in at least one., • Strong experience with SQL, data modeling, and cloud infrastructure (AWS, GCP, or Azure), • Hands-on experience with generative AI: you have built RAG systems, AI agents, prompt engineering pipelines, fine-tuned models, or similar. This is not a "nice to have," it is core to the role., • Experience with data engineering, integrations, ETL/ELT pipelines, and working with messy, real-world data, • Experience with data science and ML: NLP, recommender systems, classification, regression, neural networks. You don't need to be a research scientist, but you should be comfortable selecting, training, and deploying models., • You have owned production systems. You know what it means to deploy, monitor, debug, and maintain software that real users depend on., • You are comfortable in client-facing environments. You can explain technical trade-offs to a CEO, scope a solution with a business stakeholder, and present a demo to a PE partner., • Experience managing or mentoring other engineers is a strong differentiator. You will be expected to elevate the technical bar of the broader team., • B.S. or M.S. in Computer Science, Engineering, or a related technical field, • Legally authorized to work in the US What Sets the Best Candidates Apart: The engineers who thrive at SaxeCap are a specific breed. They combine deep technical skill with business intuition and client presence. The strongest signals we look for: • Production over theory. You have shipped AI systems that real users and real businesses depend on. Kaggle competitions and research papers are fine, but we care most about code running in production with measurable impact., • Breadth and speed. You can pick up a new domain, a new tech stack, or a new problem type and be productive in days, not months. You've worked across multiple problem areas and can context-switch without losing quality., • Full-stack AI fluency. You don't just build models. You build the data pipelines that feed them, the APIs that serve them, the frontends that expose them, and the monitoring that keeps them running. You think in systems, not components., • Client-facing instinct. You can sit in a room with a CFO or a PE partner, understand what they actually need (not just what they say they need), and translate that into a technical plan on the spot. The best FDAIs at SaxeCap are as comfortable in a boardroom as they are in a terminal., • Builder DNA. Open-source contributions, side projects, hackathon wins, or a startup attempt. You build things because you can't help it. Compensation & Growth: SaxeCap offers highly competitive compensation, and you will work directly with our senior leadership from day one, with significant client exposure and rapid professional development. The team is lean by design, there are no layers between you and impact. You will get more reps across AI techniques, industries, and business problems in one year at SaxeCap than in five years at a typical tech company.

Leverage Verasight’s data pipelines and processing procedures to own the data collection and quality process from end to end, including: building contact lists and sampling frames, monitoring survey fielding, cleaning and analyzing survey response data, writing methodology documentation, and prepa

We're hiring a Remote Data Scientist for a fast-growing, well-funded fintech company. This is a hands-on, non-client-facing seat on a small data team - you'll apply Python, SQL, and applied statistics/ML to real product and risk questions, working closely with engineers and analysts, and presenting

Description Remote Our client seeks a Principal Data Scientist to scale Data Science and AI capabilities for end-to-end payment optimization. The role will collaborate with ML engineers and product partners to design and deploy real-time models and intelligent decision engines, drive strategy and roadmaps, lead cross-functional initiatives, and mentor senior data science talent. The position balances strategic leadership with hands-on contribution across architecture, design reviews, code reviews, and select implementation to deliver production-grade ML solutions. This is a contract to hire opportunity. Applicants must be willing and able to work on a w2 basis and convert to FTE following contract duration. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance. Rate: $85.00 to $95.00/hr. w2 Responsibilities • Define technical vision and strategy for data-driven product initiatives focused on payment optimization, aligned to business goals., • Develop scalable and reusable capabilities for real-time ML models including classification, ranking, optimization, rapid experimentation, and continuous monitoring., • Oversee and contribute to conceptualization, development, deployment, operation, validation, and maintenance of ML models and update systems., • Establish and enforce best practices for ML modeling while evaluating and adopting modern tools, frameworks, and infrastructure., • Foster a culture of innovation, experimentation, and collaboration while mentoring an elite team of data scientists., • Partner with product, engineering, data, and compliance teams to integrate ML into products and communicate complex concepts to varied audiences., • Collaborate with Data Science leaders to establish an operating model for ML R&D that optimizes end-to-end delivery of business value. Experience Requirements • Bachelor’s or master’s degree in Computer Science, Statistics, Mathematics, Engineering, or related field. PhD preferred., • 7+ years in ML research or engineering with 5+ years building large-scale, real-time ML systems in production, including hands-on experience., • Expertise in machine learning, statistical modeling, and data analysis with strong experience across the ML lifecycle and experimentation., • Proficiency in Python (Pandas, NumPy, scikit-learn) and strong SQL experience. NoSQL or graph databases are a plus., • Demonstrated ability to lead solution design and execution, translating complex business requirements into actionable technology solutions., • Exceptional communication skills with the ability to influence and collaborate across technical and business audiences, including executives., • Bonus: Experience in payments, fintech, or financial services. Knowledge of payment systems such as authorization lifecycle, tokenization, fraud and risk, and real-time payments. Experience with cloud platforms including AWS, GCP, Snowflake, Databricks, or Vertex AI. Agile development experience. Background in large companies, mature ML teams, or regulated industries. Education Requirements • Bachelor’s or master’s degree in a relevant field. PhD preferred.

Junior Data Scientist 📍 Remote (United States) | Full-Time About the Role We're looking for a Junior Data Scientist to join a growing analytics team focused on building data-driven solutions and improving business performance through modern technologies. This role is ideal for someone who enjoys working with data, automation, and emerging AI tools in a collaborative, fast-paced environment. You'll work alongside analysts, engineers, and business stakeholders to support reporting, forecasting, automation, and advanced analytics initiatives across different business areas. Key Responsibilities • Analyze and interpret large datasets to support business decision-making, • Develop and maintain automated workflows using Python and SQL, • Create dashboards, reports, and visualizations using BI and analytics tools, • Support predictive analytics, segmentation, and forecasting projects, • Assist in building scalable reporting and data processing solutions, • Collaborate with technical and non-technical teams to translate business needs into data solutions, • Contribute to the maintenance and optimization of data models and pipelines Requirements (Must-Have) • Experience working with Python for data analysis, scripting, or automation, • Strong SQL knowledge and experience querying relational databases, • Familiarity with business intelligence or data visualization tools (e.g. Power BI, Tableau), • Basic understanding of machine learning concepts (e.g. regression, classification), • Foundational knowledge of statistics (hypothesis testing, distributions, correlation), • Strong analytical thinking and problem-solving ability, • Clear communication skills — able to explain data insights to non-technical audiences Nice-to-Have • Understanding of cloud-based analytics or modern data platforms (AWS, GCP, Azure), • Interest in AI-enabled workflows, automation, or applied data science, • Prior exposure to predictive modeling or forecasting projects What We Offer • Remote and flexible working environment, • Opportunity to work on modern analytics and AI-focused projects, • Supportive, collaborative team culture, • Professional development and learning opportunities, • Exposure to cloud technologies, automation, and scalable data solutions, • Career growth within an expanding team, • Performance-based incentives, • Wellness and work-life balance support --- About Why Hiring At Why Hiring, we connect talented individuals with remote job opportunities, simplifying the job search and helping professionals find fulfilling roles regardless of geography. Why Hiring does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity, or any other status protected by law.

Title: Data Scientist Location: Remote US Duration:12 months Compensation: $55-75/hr Work Requirements: US Citizen, GC Holders or Authorized to Work in the U.S. No sponsorship available ABOUT THIS FEATURED OPPORTUNITY We are seeking a proactive, technically strong Data Scientist to support a Scaled Operations organization focused on global vendor operations, including content moderation, workforce planning, and operational performance. This role will work across both Data Science and Data Engineering, with a focus on analyzing operational data, developing performance benchmarks, maintaining dashboards, and troubleshooting vendor-facing data challenges. A key area of focus will be processes surrounding Average Handling Time (AHT); analyzing how long specific vendor tasks should take, working with the underlying data and dashboards, partnering with vendor stakeholders, and establishing and publishing updated benchmarks. THE OPPORTUNITY FOR YOU In this role, you will: • Analyze operational datasets to identify trends, performance gaps, anomalies, and opportunities for improvement., • Support measurement and benchmarking initiatives, including AHT and task-level performance benchmarks., • Build, maintain, and analyze dashboards used to monitor vendor and operational performance., • Partner with vendor managers and cross-functional stakeholders to translate operational questions into data-driven insights and recommendations., • Establish, validate, and publish new operational benchmarks., • Troubleshoot vendor-facing data challenges, including missing or inconsistent data, system discrepancies, permissions/access issues, and potential bugs., • Support data engineering needs related to vendor data and operational reporting., • Proactively identify additional issues, risks, and opportunities and independently drive work toward resolution., • Leverage AI-enabled tools where appropriate while maintaining strong analytical judgment and understanding of the underlying data. KEY SUCCESS FACTORS • 3-5+ years of relevant industry experience in Data Science, Data Analytics, Analytics Engineering, Data Engineering, or a related field., • Strong SQL and data analysis skills, including independently querying, manipulating, validating, and troubleshooting complex datasets., • Dashboarding and operational measurement experience, including analyzing performance metrics and developing data-driven benchmarks., • Working knowledge of data engineering concepts, with the ability to investigate missing or inconsistent data, permissions/access challenges, discrepancies, and potential bugs., • Highly proactive, curious, and independent problem solver who can take an ambiguous request, determine what needs to be investigated, uncover additional problems or opportunities, and drive work forward with limited direction. NICE TO HAVES • Experience supporting scaled operations, vendor operations, workforce planning, content moderation, or other large-scale operational environments., • Experience partnering directly with vendor managers or external-facing operational teams., • Experience working in an environment where Data Science, Analytics, and Data Engineering responsibilities overlap., • Experience using AI-enabled tools to improve analytical workflows while maintaining independent reasoning and validation., • Experience within a large, complex technology or product organization. About INSPYR Solutions Technology is our focus and quality is our commitment. As a national expert in delivering flexible technology and talent solutions, we strategically align industry and technical expertise with our clients' business objectives and cultural needs. Our solutions are tailored to each client and include a wide variety of professional services, project, and talent solutions. By always striving for excellence and focusing on the human aspect of our business, we work seamlessly with our talent and clients to match the right solutions to the right opportunities. Learn more about . INSPYR Solutions provides Equal Employment Opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, or any other protected status. INSPYR Solutions complies with all applicable laws governing nondiscrimination in employment in every location in which the company has facilities. Applicants requiring reasonable accommodation during the application or interview process should contact for assistance. Information collected and processed through your application with INSPYR Solutions (including any job applications you choose to submit) is subject to INSPYR Solutions' Privacy Policy and INSPYR Solutions' AI and Automated Employment Decision Tool Policy: https://www.inspyrsolutions.com/policies/. By submitting an application, you are consenting to being contacted by INSPYR Solutions through phone, email, or text.

As Scientist / Lead, Translational Data Platforms, you will play a pivotal role in shaping how researchers interact with complex clinical and multi-omic datasets, influencing platform strategy, developing innovative analytical capabilities, and helping build technologies that enable the next generat

We are seeking an experienced AI Data Scientist to join Deltek’s growing AI Center of Excellence team to design, build, evaluate, and optimize enterprise AI solutions leveraging Large Language Models (LLMs), AI Agents, Retrieval-Augmented Generation (RAG), multimodal AI, Opensource AI Models, and

Mentor and guide junior data scientists, fostering technical excellence and continuous learning within the team. Optimize and automate data pipelines using Python, PySpark, and R, ensuring efficient data processing and feature engineering. Design and implement robust statistical models and machine l

Assess data analysis, experimentation approaches, and data modeling techniques. Data Scientists and Quantitative Professionals. Create challenging prompts, datasets, and reference solutions.

Join the team at RoboStrategy as Data Scientist, Associate.RoboStrategy (Nasdaq: BOT) is on a mission to become the leading public investment vehicle for robotics.We provide investors with access to what we believe are the most transformative companies in robotics, many of which remain private and i

We are seeking a Data Scientist to develop and evaluate AI solutions for legal content workflows. Our client, a major legal company, is actively looking for a Senior Data Scientist to join their team! This is a fully remote position, however candidates must be located in the US and able to work EST

You will work as a forward deployed data scientist: embedded with enterprise clients, turning ambiguous business problems into working analytical and AI solutions, and staying with the work until it runs in their environment.This is a hands-on senior role.You will own problems end to end — scoping

The Senior Scientist, Biologics Analytical Development, supports the development of recombinant protein production processes and analytical strategies for biologic therapeutics. This role is responsible for analytical method development, product characterization, and analytical support for process development activities involving microbial and mammalian expression systems. The position contributes to the advancement of innovative therapies addressing unmet medical needs. Key Highlights: Analytical method development and optimization Protein and conjugate characterization using HPLC, CE, Mass Spectrometry, and biophysical characterization techniques Support of upstream and downstream process development CRO/CMO oversight and technology transfer activities GMP manufacturing support and regulatory documentation contributions Essential Duties & Responsibilities Support extended characterization studies of recombinant proteins and protein conjugates using a variety of analytical techniques including LC-MS peptide mapping, U/HPLC, SEC, IEX, CE-SDS, iCIEF, GC/GC-MS, and biophysical techniques Process and review analytical data utilizing modern chromatographic and mass spectrometry CDS/MS software platforms Write and approve technical reports, SOPs, and method protocolsDevelop, optimize, and qualify analytical methods for biologic products. Characterize and quantify product and process related impuritiesSupport upstream and downstream process development programs. Manage analytical activities performed by CROs and support analytical transfers to CROs and CMOs. Review analytical data and reports supporting GMP manufacturing activities. Author and/or review CMC sections of regulatory submissions. Independently design, execute, and analyze laboratory experiments. Evaluate complex scientific data and apply sound technical judgment. Collaborate with cross-functional teams and external partners. Author and approve technical reports, protocols, and scientific documentation. Maintain compliance with applicable regulatory and quality requirements. Support resource planning, equipment identification, and organizational initiatives. Lead projects, mentor team members, and provide training as needed. Skills: Minimum 5 years of experience within the biotechnology or pharmaceutical industry, preferably in process development. Applicable postdoctoral experience may be considered toward the experience requirement. Demonstrated technical expertise, scientific creativity, and independent thinking. Strong problem-solving, organizational, and analytical abilities. Excellent written and verbal communication skills. Ability to effectively communicate scientific concepts to both technical and non-technical audiences. Strong interpersonal and collaboration skills. Proficiency with Microsoft Word, Excel, and PowerPoint. Ability to work effectively in a fast-paced, team-oriented environment. Preferred Qualifications Experience working in an FDA-regulated environment. Knowledge of current GMP requirements and laboratory practices. Experience contributing to regulatory submissions. Prior leadership or management experience. Education: PhD in a scientific or engineering discipline required. Equivalent experience may be considered. Exceptional candidates without a PhD may be considered based on demonstrated capabilities and significant relevant experience.

ML Scientist, Statistical Modeling, Predictive Modeling, Paneling, Normalization, Cohorting, Causal Inference, Synthetic Control, Uplift Modeling, Transaction Data, Behavioral Modeling, Forecasting, Representation Learning, Privacy Preserving ML, Cleanrooms, Production ML Pipelines. Principal Data S

Applied Scientist (Remote | $245–$280/hr) Position: Applied Scientist Type: Contractor Compensation: $245–$280 per hour Location: Remote About the Opportunity An AI-focused project is seeking Applied Scientists to contribute expertise in advanced analytics, experimentation, statistics, and machine learning. Contractors will help improve next-generation AI systems by evaluating model outputs, developing high-quality datasets, and providing expert feedback. Prior AI experience is not required. Key Responsibilities • Design and execute statistical analyses to uncover insights from complex datasets., • Develop, validate, and evaluate machine learning models for business and research objectives., • Apply data modeling techniques and manage data transformations using Python and Pandas., • Collaborate with stakeholders to establish experimentation frameworks and analyze outcomes., • Document methodologies, findings, and recommendations clearly and accurately., • Review peer contributions and provide constructive technical feedback., • Deliver reproducible code and organized analytical reports., • Evaluate AI model outputs involving statistics, machine learning, experimentation, and quantitative reasoning., • Create expert-level prompts, datasets, and reference solutions., • Identify flawed methodologies, statistical errors, and weaknesses in quantitative reasoning., • Provide structured feedback to improve AI model performance. Required Qualifications • Strong proficiency in Python and data analysis., • Knowledge of machine learning, statistics, experimentation, and data modeling., • Experience with Pandas and related data science tools., • Strong analytical, problem-solving, and quantitative reasoning skills., • Excellent written and verbal communication skills. Preferred Qualifications • At least one year of experience at a leading company in technology, finance, or research., • Proficiency with Python libraries such as Pandas and scikit-learn., • Demonstrated experience in applied statistics, experimental design, and machine learning., • Experience developing, tuning, and evaluating machine learning models., • Ability to work with structured and unstructured data., • Experience collaborating on cross-functional or open data science projects., • Advanced academic background or practical experience in data science, applied mathematics, or a related field. Compensation • Hourly compensation of $245–$280., • Remote, contractor-based engagement. Application Process The application process was not specified in the provided listing.

About Sapio Sciences Sapio Sciences is on a mission to accelerate scientific drug discovery and high-throughput clinical and diagnostics for our clients and partners. The Sapio team consists of expert and highly collaborative scientists, software developers, and professionals passionate about providing a best-in-class lab informatics platform and industry-specific solutions. Sapio is one of the few software providers to offer a truly unified and highly configurable lab informatics platform and a broad suite of purpose-built solutions. The Sapio platform makes it easy for scientists, laboratory, and bio/informatics professionals to streamline and manage their end-to-end laboratory operations, from instrument data integration to workflow and experiment setup to sample and materials management, data management, and scientific data analysis and reporting. Working at Sapio At Sapio, we’re not just building lab informatics solutions. We’re creating tools made for the scientist and motivated to make the world a better place. We understand that lab informatics is about more than managing data or connecting workflows. It’s about making life easier for the scientist and making scientific progress faster for everyone. Our platform delivers the levels of configurability, usability and insight that scientists have only ever dreamed of. We’re a team of scientists, developers and innovators who question convention and stay focused on what matters most - advancing drug discovery science. We challenge the status quo and respond to the needs at the heart of science with powerful solutions that are simple to use, effortless to evolve and downright easy to love. As part of the Sapio team, you’ll work in a collaborative and forward-thinking environment where your ideas are valued, your growth matters and your work makes a difference. We’re proud to partner with leading labs around the world, from ambitious start-ups to global organisations, who trust Sapio to support discovery, development and diagnostics with industry-first science-aware solutions. About the Role As Head of Sales, you own the sales motion for Sigmatic Sciences end to end — carrying the revenue number and building the team, methodology, and pipeline that deliver it. This is a global mandate weighted toward the United States and European markets, spanning new business, expansion, and retention across our Strategic Account Managers and Scientific Liaisons. You will define how Sigmatic sells: the account planning, engagement model, and playbooks that make growth repeatable and forecastable. You will lead from the front — coaching the team while personally driving the most complex, highest-value deals. Marketing, Product, and Customer Success are your closest partners, and you will work in lockstep with them to convert demand, shape the roadmap, and secure long-term customer value. Sales execution, and the number, are yours. This is a pivotal hire. You will build the growth engine that scales Sigmatic globally, turning a genuinely differentiated platform into commercial momentum in a market that is only beginning to grasp what lab-in-the- loop can do. Working Location This is a remote role based on the East Coast of the United States, with regular travel to meet your global team, key customers, and Sapio leadership. Our people are distributed worldwide, with physical offices in York, PA; Fort Lauderdale; and London. Responsibilities About the Role • Own the number. Carry and deliver Sigmatic's revenue targets across new business, expansion, and net revenue retention and take personal responsibility for the strategic accounts that anchor the annual plan., • Define how Sigmatic sells. Establish the account-planning methodology, engagement cadences, and expansion playbooks that make growth predictable, with Scientific Liaisons deployed to lead business-value conversations at the core of the go-to-market model., • Run a disciplined operating rhythm. Own forecasting, pipeline hygiene, CRM discipline, and a visible, relentlessly managed set of KPIs that underpin dependable performance., • Own executive relationships. Serve as the senior point of partnership and escalation on your most important and most complex accounts., • Partner with leadership. Work with the CCO and wider leadership to set targets, shape priorities, and report on the health of the sales portfolio., • Collaborate across the go-to-market team. Work closely with Marketing, Product, and Customer Success — converting demand into pipeline, feeding customer and market intelligence into the roadmap, and aligning on retention and expansion — without owning those functions., • Represent Sapio and Sigmatic. Show up with credibility at industry events, customer meetings, and executive briefings as a senior commercial leader. Requirements • A track record of leading enterprise B2B SaaS sales and consistently meeting or beating revenue, net revenue retention, and expansion targets in complex, multi-stakeholder accounts., • Experience building and scaling a distributed sales or presales team across multiple geographies and cultures., • Fluency in a recognized enterprise sales methodology (e.g., MEDDIC, Challenger, Force Management), with strong command of executive-level engagement and multi-year commercial negotiation., • The ability to build the playbooks, cadences, and account plans a scaling team runs on — and to lead from the front on the hardest deals., • Enough command of agentic AI, lab-in-the-loop, and in-silico approaches to sell their value credibly to scientific and executive buyers in therapy design and development., • Experience selling into life sciences, biopharma, or diagnostics strongly preferred; familiarity with lab informatics and an existing network in pharma or biotech are distinct advantages. Required Skills & Attributes • Exceptional people leadership — you inspire, develop, and hold a distributed team accountable to a high bar, • Strong executive presence and the credibility to engage C-suite and senior stakeholders as a peer, • Commercial acumen across account planning, renewals, and expansion, with a data-driven approach to, • forecasting and performance, • Clear, persuasive communication that builds trust quickly, both internally and with customers, • A collaborative operator who influences without authority and thrives cross-functionally, • Comfortable in a fast-paced scale-up where you build structure as you grow, • Willing to travel regularly across the US and to Europe to support your team and key accounts Our People At Sapio Sciences, our people are at the heart of everything we do. Our lab informatics solutions are powered not just by technology, but by a shared commitment to our core values—what we proudly call The Sapio Seven, aka EMBRACE: • Embrace the future • Make a difference • Be true partners • Remember why we’re here • Act with empathy • Commit to transparency • Excel in quality These values shape how we work, how we grow, and how we deliver impact for our clients every day. Reasonable Adjustments We are committed to ensuring an inclusive and accessible recruitment process. If you require any reasonable adjustments, at any stage across the application, interview & assessment processes then please let us know. We will work with you to support your needs in confidence. Diversity, Equity & Inclusion We do not discriminate based on race, colour, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, disability, or any other status protected by law or regulation. We intend that all qualified applicants be given equal opportunity and that selection decisions are based on job-related factors. We are committed to creating a diverse and inclusive workplace and encourage applications from all qualified individuals. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Overview THE ROLEAt Great Dane, we rely on makers and we’re calling on them to join our expanding team, the time has never been better to Embrace Your Great and work in an environment with the highest safety standards in the industry.The Position: The AI Architect defines the technical architecture, standards, and reusable patterns for enterprise AI, machine learning, and generative AI solutions. This role ensures AI solutions are secure, governed, scalable, supportable, and aligned with enterprise data and application architecture. The AI Architect partners with Enterprise Architecture, Data Architecture, Data and AI Governance, and Application Development to translate approved AI opportunities into practical solution designs, implementation guidance, and supporting architecture artifacts. Responsibilities WHAT YOU’LL DODefine the reference architecture for AI/ML and generative AI workloads, including the Durable Hub - Great Dane's central data and integration hub.Ensure enterprise data is AI-ready — well-governed, well-modeled, and accessible — by partnering closely with the Data Architect and Data Governance Committee.Partner with the Data Architect to ensure the enterprise ontology and semantic models are effective for AI consumption — defining how ontology concepts ground LLMs, RAG pipelines, and agent reasoning, and feeding gaps or ambiguities back into the ontology while the Data Architect retains ownership of its authoritative definition and governance.Evaluate, select, and integrate AI/ML platforms, frameworks, and services; define build-vs-buy guidance.Establish responsible AI practices, including governance, evaluation, monitoring, and controls for accuracy, bias, and data privacy.Design and prototype high-value AI use cases (e.g., predictive analytics, document/entity extraction, decision support) and partner with Development teams to shepherd them from proof of concept into production.Define MLOps/LLMOps patterns for model lifecycle, versioning, and observability, and collaborate with Development to embed them into delivery pipelines and engineering practices.Align AI architecture and delivery roadmaps with Intelligence Automation project owners and stakeholders to ensure initiatives support program priorities and deliver measurable value.Support Business Analysts in assessing and shaping AI solution opportunities by providing the technical perspective — evaluating feasibility, data readiness, implementation complexity, operational impact, and architectural fit — to inform business-value and roadmap decisions.Provide architecture direction, solution design guidance, and implementation artifacts to Development teams, partnering with engineers to co-design production-ready approaches while preserving Development ownership of engineering execution, integration, deployment, and operational support.Own and maintain the AI architecture documentation framework, including reference architectures, solution design documents, architecture decision records, technical standards, implementation patterns, integration diagrams, data flow diagrams, operational support models, and supporting artifacts required to guide delivery, governance, and long-term maintainability of AI solutions.Establish and govern documentation standards for AI solutions, ensuring architecture artifacts, technical designs, decision records, diagrams, and implementation guidance are created, maintained, versioned, and stored in approved enterprise repositories such as SharePoint and Miro.Provide technical mentorship on AI patterns to the data engineering and Development teams.Other duties as assigned. Qualifications COMPETENCIES:Transformation and Change Management: The ability to lead and execute initiatives that drive significant organizational change, including cultural, process, and structural transformations. Involves assessing readiness, creating a vision, aligning stakeholders, and applying structured change management frameworks.Operational Rigor: The disciplined application of structured processes, controls, and performance standards to ensure consistency, quality, and efficiency in operations. Focuses on accountability, compliance, and continuous improvement.Strategic Capability: The capacity to think critically, anticipate future trends, and develop strategies that position the organization for long-term success while balancing short- and long-term needs.Cultural Fit: The alignment of personal values, behaviors, and working style with the organization’s mission, vision, and culture. Adapts and thrives within the environment while constructively influencing its evolution.Ability to Build Sponsorship: The ability to gain the support, advocacy, and active involvement of key stakeholders for initiatives, strategies, or change efforts. Builds trust, demonstrates credibility, and aligns initiatives with stakeholder priorities.YOUR SKILLS & ABILITIES (REQUIRED QUALIFICATIONS)Education: Bachelor's degree in Computer Science, Data Science, Machine Learning, or a related field; Master's preferred.Experience: 7+ years in software/data engineering or data science; 3+ years architecting and delivering production AI/ML or generative AI solutions. Demonstrated experience integrating AI with enterprise data platforms and deploying models at scale.Skills: Strong grounding in ML and generative-AI patterns (RAG, embeddings, model evaluation), MLOps/LLMOps, and cloud AI services (AWS preferred). Proficiency in Python and SQL; familiarity with streaming and lakehouse architectures (Kafka/Confluent, medallion, Iceberg). Working knowledge of data governance and responsible-AI principles. Excellent stakeholder communication. AWS certification a plus.Travel: Occasional; typically less than 10%.CAREER PATHWAYS:Prerequisite Positions: Senior Data Scientist, ML Engineer, or Data/Solutions Architect.Potential Growth Opportunities: Principal AI Architect, Head of AI/ML, or Enterprise Architect.PHYSICAL/MENTAL REQUIREMENTS:Office and plant environment.Keyboarding, lifting, standing, bending, walking.Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.ABOUT GREAT DANEWith a history dating back to 1900, Great Dane has established itself as a transportation solutions leader of today – delivering innovative products and exceptional services that help our customers and employees succeed. We not only engineer durable and high-quality trailers and truck bodies; we foster relationships that last a lifetime.WHY WORK FOR US?Great Dane is a leading manufacturer of dry-freight vans, refrigerated trailers, and flatbeds with 10 manufacturing facilities and 20 service centers throughout the United States. With a legacy like ours comes a dedication to the hard-working individuals that make Great Dane what it is today. Our jobs are waiting to be filled by driven, challenge-focused & enthusiastic people like you.Our culture is comprised of “Champions” and offers a rewarding workplace rooted in core values of safety, leadership, integrity, quality, and passion. Every employee has opportunities to learn, grow, succeed and be engaged in a collaborative environment.BENEFITS OVERVIEWCompetitive compensationBenefits, including but not limited to dental, vision, and medical with employer contributionsRetirement programs, including a Pension Plan and 401(k) Plan with employer matchTuition ReimbursementPaid holidays and vacationAnd more!Great Dane is an Equal Opportunity EmployerJob SummaryID: 2026-4567Category: Information SystemsPosition Type: Regular Full-Time

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