Trabajos data scientist en Irving, TexasCrear alertas

Bachelor’s degree in Civil Engineering or a closely related engineering field (Master’s preferred for some roles). IT consulting firm delivering top-notch, Machine Learning Engineer, iOS and Android, data scientist, Developer and Civil Engineering solutions to industry giants including Delta, Go

Pride Health is hiring a Medical Lab Scientist to support our client’s medical facility in Irving TX 75063 This is a 3-month assignment with the possibility of a contract-to-hire opportunity, and it's a great way to start working with a top-tier healthcare organization! Job Title: Medical Lab Scientist - MUST BE ASCP /MLT certified Location: Irving TX 75063 Pay Range: $30-$40 per hour Schedule: Tuesday- Saturday, 1p- 9:30 0m(Central) Duration: 3 Months+ Job Responsibilities • Perform specimen handling, processing, and analysis following laboratory SOPs and CLIA regulations., • Review, validate, and release test results accurately and on time., • Maintain complete and organized records of test data, QC, calibrations, and maintenance., • Adhere to all CLIA, HIPAA, OSHA, and internal safety and quality guidelines., • Troubleshoot and resolve testing or equipment issues; escalate when necessary., • Report STAT and critical results per department policy., • Participate in quality assurance, safety training, and departmental meetings., • Assist with audits, regulatory inspections, and cross-departmental communication., • Strong understanding of clinical laboratory testing and hematology procedures., • Knowledge of Quality Control (QC) and Quality Assurance (QA) principles., • Proficient in multiple computer systems / LIS and data entry accuracy., • Excellent communication, organization, and multitasking skills., • BS in Medical Technology preferred; or BS/BA in Chemistry or Biology, or Associate’s degree in Laboratory Science., • Must meet CLIA personnel qualification standards (42 CFR 493.1433)., • ASCP or AMT certification strongly preferred or eligible., • Minimum 1 year of high-complexity clinical laboratory experience required., • Hematology experience is mandatory. Pride Global offers eligible employees comprehensive healthcare coverage (medical, dental, and vision plans), supplemental coverage (accident insurance, critical illness insurance, and hospital indemnity), 401(k)-retirement savings, life & disability insurance, an employee assistance program, , legal support, auto ,home insurance, pet insurance, and employee discounts with preferred vendors.

Mercor is hiring experienced Python Engineers to support a variety of high-impact research collaborations with leading AI labs. Freelancers will help improve AI systems through work extending coding benchmarks that reflect real-world development across diverse languages and domains. This is a unique opportunity to apply your engineering expertise toward shaping the next generation of intelligent systems. Key Responsibilities - Develop and validate coding benchmarks in Python by curating issues, solutions, and test suites from real-world repositories - Ensure benchmark tasks include comprehensive unit and integration tests for solution verification - Maintain consistency and scalability of benchmark task distribution - Provide structured feedback on solution quality and clarity - Debug, optimize, and document benchmark code for reliability and reproducibility Ideal Qualifications - 3–10 years of experience as a backend software engineer, ML engineer, or applied data scientist - Degree in Software Engineering, Computer Science, or a related field - Strong proficiency in Python - Experience with debugging, testing, and validating code - Comfortable with technical writing and attention to detail Project Timeline - Start Date: Immediate - Duration: 1 month - Commitment: Part-time (15–20 hours/week) - Schedule: Fully remote and asynchronous – flexible working hours Compensation & Contract - $80 per hour plus lucrative bonus per approved task (1 task takes approximately 1 hour to complete) - Median average pay inclusive of bonuses is $200/hr - Independent contractor - Daily payment via Stripe Connect Application & Onboarding Process - Upload your resume - AI interview: A short, 15-minute conversational session to understand your background, experience, and interest in the role - Brief assessment testing real-world coding ability, technical depth, and debugging approach - Follow-up communication within a few days with next steps and onboarding details About Mercor Mercor is a San Francisco-based company specializing in connecting elite professionals with cutting-edge AI initiatives. Our investors include Benchmark, General Catalyst, Adam D’Angelo, Larry Summers, and Jack Dorsey. Thousands of professionals across engineering, research, and creative fields have partnered with Mercor on frontier projects shaping the future of AI. Apply today and leverage your software engineering expertise to help build the future of AI-driven systems!

About the Role At Mercor, we are partnering with top AI labs in applying AI to complex scientific challenges to build a state-of-the-art benchmark to evaluate the capabilities of the lab’s AI models in the field of bioinformatics. Our goal is to test a model's ability to autonomously design and execute complex bioinformatics workflows, starting from raw sequencing data and a natural language prompt. This project requires a sophisticated blend of tool proficiency, deep biological domain knowledge, and rigorous scientific reasoning. We are seeking talented researchers to help us create these benchmark tasks using real-world, published scientific data. A brief 15-minute interview precedes candidate selection, with decisions typically made within four days following assessment completion. Currently, applicants must be based in the U.S., UK, Canada, Australia or New Zealand. Why You’re a Great Fit You're a strong candidate if you: - Must be a current graduate student (M.S. or Ph.D.) or hold a higher degree (e.g., Postdoctoral Fellow, Research Scientist) in Bioinformatics, Computational Biology, Genomics, or a related quantitative field. - Experience using bioinformatics command line tools - Demonstrate exceptional attention to detail and rigorous problem-solving skills. - Excel in both written and verbal communication. Role Highlights - Flexible workload: 10–20 hours weekly, with the potential to scale to 40 hours. - Fully remote and asynchronous scheduling. - Initial commitment of 1–2 months, with opportunities for extension. Compensation and Legal Details - You will be legally classified as an hourly contractor for Mercor - We will pay you out at the end of each week via Stripe Connect About Mercor Mercor is a $2B company that connects elite talent with leading AI research labs and is headquartered in San Francisco, CA. Our distinguished investors include Benchmark, General Catalyst, Peter Thiel, Adam D’Angelo, Larry Summers, and Jack Dorsey. Apply today to leverage your skills in advancing revolutionary AI technologies!

Job Description: AI Task Evaluation & Statistical Analysis Specialist ## Role Overview We're seeking a data-driven analyst to conduct comprehensive failure analysis on AI agent performance across finance-sector tasks. You'll identify patterns, root causes, and systemic issues in our evaluation framework by analyzing task performance across multiple dimensions (task types, file types, criteria, etc.). ## Key Responsibilities - Statistical Failure Analysis: Identify patterns in AI agent failures across task components (prompts, rubrics, templates, file types, tags) - Root Cause Analysis: Determine whether failures stem from task design, rubric clarity, file complexity, or agent limitations - Dimension Analysis: Analyze performance variations across finance sub-domains, file types, and task categories - Reporting & Visualization: Create dashboards and reports highlighting failure clusters, edge cases, and improvement opportunities - Quality Framework: Recommend improvements to task design, rubric structure, and evaluation criteria based on statistical findings - Stakeholder Communication: Present insights to data labeling experts and technical teams ## Required Qualifications - Statistical Expertise: Strong foundation in statistical analysis, hypothesis testing, and pattern recognition - Programming: Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis - Data Analysis: Experience with exploratory data analysis and creating actionable insights from complex datasets - AI/ML Familiarity: Understanding of LLM evaluation methods and quality metrics - Tools: Comfortable working with Excel, data visualization tools (Tableau/Looker), and SQL ## Preferred Qualifications - Experience with AI/ML model evaluation or quality assurance - Background in finance or willingness to learn finance domain concepts - Experience with multi-dimensional failure analysis - Familiarity with benchmark datasets and evaluation frameworks - 2-4 years of relevant experience

Mercor is hiring experienced Go Engineers to support a variety of high-impact research collaborations with leading AI labs. Freelancers will help improve AI systems through work extending coding benchmarks that reflect real-world development across diverse languages and domains. This is a unique opportunity to apply your engineering expertise toward shaping the next generation of intelligent systems. Key Responsibilities - Develop and validate coding benchmarks in Go by curating issues, solutions, and test suites from real-world repositories - Ensure benchmark tasks include comprehensive unit and integration tests for solution verification - Maintain consistency and scalability of benchmark task distribution - Provide structured feedback on solution quality and clarity - Debug, optimize, and document benchmark code for reliability and reproducibility Ideal Qualifications - 3–10 years of experience as a backend software engineer, ML engineer, or applied data scientist - Degree in Software Engineering, Computer Science, or a related field - Strong proficiency in Go - Experience with debugging, testing, and validating code - Comfortable with technical writing and attention to detail Project Timeline - Start Date: Immediate - Duration: 1 month - Commitment: Part-time (15–20 hours/week) - Schedule: Fully remote and asynchronous – flexible working hours Compensation & Contract - $90 per hour plus lucrative bonus per approved task (1 task takes approximately 1 hour to complete) - Median average pay inclusive of bonuses is $200/hr - Independent contractor - Daily payment via Stripe Connect Application & Onboarding Process - Upload your resume - AI interview: A short, 15-minute conversational session to understand your background, experience, and interest in the role - Brief assessment testing real-world coding ability, technical depth, and debugging approach - Follow-up communication within a few days with next steps and onboarding details About Mercor Mercor is a San Francisco-based company specializing in connecting elite professionals with cutting-edge AI initiatives. Our investors include Benchmark, General Catalyst, Adam D’Angelo, Larry Summers, and Jack Dorsey. Thousands of professionals across engineering, research, and creative fields have partnered with Mercor on frontier projects shaping the future of AI. Apply today and leverage your software engineering expertise to help build the future of AI-driven systems!

A leading infrastructure solutions company is looking for an experienced candidate to develop and deliver advanced data sciences solutions in Dallas, Texas. Responsibilities include leading service improvement initiatives, managing data management platforms, and training clients on technology.

Coordinates with Data Engineers to build data environments providing data identified by Data Analysts, Data Integrators, Knowledge Managers, and Intel Analysts. Data Scientist Job Duties: Formul

Coordinates with Data Engineers to build data environments providing data identified by Data Analysts, Data Integrators, Knowledge Managers, and Intel Analysts. Defines company data assets (data models), spark, sparkSQL, and hiveSQL jobs to populate data models. Data Scientist Job Duties:

We're committed to attracting the most creative, talented, and motivated students for our Associate Data Scientist and Data Scientist roles. Including: Understanding business issues, proposing technical solutions, data wrangling, data cleaning, data analysis, feature engineering, model selection, mo

In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. Directing data engineers and other data scientists to deliver efficient solutions to meet client requirements;. Managing teams to process

Provides expert technical guidance and integrates with a team of data scientists, applied AI scientists, engineers, and analysts responsible for multiple technologies. Applies expert business skills and consulting methodologies to collect and analyze data to determine the applicability, functionalit

We are looking for a Data Scientist who will support our client teams with insights gained from analyzing data leveraging advance analytics techniques. Use Data driven insights to drive business outcomes and communicate the same to stakeholders. Develop processes and tools to create and monitor data

What You’ll Do** - Analyze large, complex datasets to uncover patterns, develop insights, and inform modeling direction - Build predictive models, statistical analyses, and machine learning pipelines across tabular, time-series, NLP, or multimodal data - Design and implement robust validation stra

Duration: 7 Months Location: Dallas, TX (onsite in a hybrid model) Job Description: The client is looking for a Decision Scientist to join their Marketing & Commercial Decision Science and Analytics Engineering group.

We are hiring for an experienced Data Scientist, Machine Learning Engineer, or AI Engineer with a knack for developing automated tools with an interest in the cybersecurity space.You will be joining a global enterprise financial investment organization and working with a premier team to both develop

Job DescriptionCompany Description We are a passionate team of 300+ engineers, mathematicians, data analysts, project managers, and business consultants. But more importantly, we are active listeners, deep thinkers, and courageous problem solvers. The Resultant team purposefully comes together to produce a positive outcome. Our name symbolizes our commitment to empathy and collaboration—of not just delivering our clients with the best solutions, but to deeply listening to them, understanding their needs, and learning from each other in the process. The force of Resultant comes from the combined knowledge, passion, and innovation of our team and partners. Together, we partner with clients in the public and private sectors to help them overcome their most complex challenges, empowering our clients to drive meaningful change in their organizations and communities. In everything you do, you’ll help your clients, colleagues, and communities thrive. Resultant was founded as KSM Consulting in 2008. Job Description At Resultant, we are fearless problem solvers. We are passionate about helping our clients solve their toughest problems, while empathizing with people our solutions will help. Data analytics is a core component of how we do this. We are looking for a Senior Data Scientist / Machine Learning Engineer (DS/MLE) to add to our talented team of team of Data Scientists, Data Engineers, and Data Architects to solve some of the most exciting and challenging problems faced by companies and governments in today’s fast-paced environment. As a Senior DS/MLE, you will have the opportunity to develop novel machine learning and AI solutions and deploy them to production applications and systems. Here is what a typical day for you might look like: * Engaging directly with current and prospective clients to understand business needs, translate them into technical requirements, and communicate findings in a clear, actionable way * Partnering with internal and client stakeholders to shape solutions, develop proposals, and contribute to go-to-market initiatives * Design, develop and deploy efficient data pipeline for both structured and unstructured data * Productionize machine learning research in both on premises and cloud environments * Rapid prototyping solutions and integrating of new data sources * Drive optimization, testing and tooling to improve quality of solutions * Develop and apply machine learning and advanced analytics algorithms to solve problems you have never seen before * Collaborate with data architects and software developers to plan and construct the architecture of model deployment * Develop and support APIs to serve models and other data solutions * Continuously learning and adopting new tools and technologies to stay ahead in a rapidly evolving AI landscape Qualifications Education and Experience: Required * Bachelor’s degree (and preferably an advanced degree) in Computer Science, Engineering, or in a quantitative field is required * 5+ years experience with software engineering in Python (additional languages like Scala/C++/R are a plus) * 3+ years experience with Databricks and/or Apache Spark * 3+ years experience with advanced analytics and modern machine learning techniques * 3+ years experience with APIs, containerization (Docker), and orchestration (Airflow) * 3+ experience with relational databases and SQL (Postgres, Redshift, SQL Server) * 3+ experience with Cloud platforms (Azure, AWS, GCP) and services * Proficient with version control * Proficient in software architecture and design patterns * Proficient on Linux for both development and operations Preferred * Experience with deploying applications on Kubernetes * Experience with Palantir Foundry * Experience with Python API development frameworks (FastAPI, Django, Flask) * Experience with NoSQL and streaming platforms, e.g., Kafka, MongoDB, Neo4j Consulting, Communication and Leadership Skills: * Experience working in a consulting or client-facing environment, collaborating directly with business stakeholders * Strong ability to translate complex technical concepts for non-technical audiences * Demonstrated experience contributing to business development efforts, including proposal writing, solutioning, and partnering with sales or account teams * Solution creativity and effective written, verbal, and presentation skills * Proven success working across diverse industries and project sizes with a collaborative, outcomes focused mindset * Entrepreneurial inclination to discover novel opportunities for applying analytical techniques to business and social problems Additional Information What you should know about Resultant: • Rezzers are humble, hungry, and smart. We solve big problems, serve lots of clients, and are entirely committed to delivering transformative outcomes., • Rezzers are team players, deeply dedicated to the mission of the organization and to helping everyone around us be successful., • Resultant compensates well, rewarding performance that delivers positive outcomes for our clients and ensuring incentives are aligned to achieve our goals., • Resultant leaders work hard, serving as a shining example of what it means to be a great Rezzer. They are servant leaders, helping their team to be successful in all possible ways., • We have a great benefits package including unlimited vacation, significant 401k contributions, and several opportunities to develop yourself., • “I love our true empathy and concern for our clients, it's very rare and appreciated. It is a pleasure to be a part of an organization like Resultant.”, • “I learn something new every single day, and I feel like I'm a part of building an organization that has legs. I appreciate that I'm consistently humbled by the talent and caliber of our team.” Equal Opportunity Employer

Job Description We are looking for a Data Scientist for one of our leading engineering clients in Irving, TX or Cary, NC. APPLY NOW! Title: Data Scientist 3 Location: Irving, TX or Cary, NC-100% onsite- Cary, NC preferred Hours: M-F regular 40 hour work week Type: Contract Pay: range $39-42.77/hour on w2 Length: 12 months- possibility to extend Screenings: no tech, full panel drug and background once hired IV process: 2 onsite IV's +optional benefits, long term contract with ability to extend or convert to full time ⭐ Must haves: • Years of experience: 5+ years (regardless of level of degree) - will accept internships as job experience, • Degree requirement: Bachelors and/or Masters are required, • Proficiency in Python, SQL, and data science libraries (e.g., Pandas, Scikit-learn, TensorFlow), • Strong foundation in statistics, probability, and machine learning, • Familiarity with cloud platforms (e.g., Azure, AWS, Snowflake) and data modeling, • experience working in at an enterprise level, • Excellent communication skills to explain technical concepts to non-technical stakeholders Job Description A Data Scientist is responsible for analyzing large volumes of structured and unstructured data to extract actionable insights, build predictive models, and support data-driven decision-making. This role blends statistical expertise, programming skills, and business acumen to solve complex problems and drive innovation. Position’s Contributions to Work Group: • A Data Scientist is responsible for analyzing large volumes of structured and unstructured data to extract actionable insights, build predictive models, and support data-driven decision-making., • This role blends statistical expertise, programming skills, and business acumen to solve complex problems and drive innovation. Why (client name removed)? “Whether it be ground-breaking products, best in class solutions or a lifelong career, you can build what matters to you at (client name removed). With 150 locations in countries around the world, what you create at (client name removedtravels and helps people around the world. You can collaborate with the best minds in the industry, complete meaningful work and continuously grow and develop through our various opportunities. Here, you can do the work that matters.” Typical Day or Week in the Role • Typical task breakdown and rhythm, • Interaction level with team, • Team Structure, • Work environment description Typical task breakdown: • Data Collection & Preparation: Gather, clean, and validate data from various sources to ensure quality and usability, • Exploratory Data Analysis: Identify trends, anomalies, and patterns in large datasets, • Model Development: Design and implement machine learning models (e.g., regression, classification, clustering, NLP) to support forecasting and decision-making, • Data Visualization: Create dashboards and reports using tools like Power BI, etc., to communicate findings, • Automation & Optimization: Develop scripts and tools to automate data processing and model deployment, • Collaboration: Work cross-functionally with product, engineering, and business teams to align data initiatives with strategic goals, • Research & Innovation: Stay current with emerging technologies and methodologies in data science and apply them to business challenges Interaction with team: • Primarily working with 10+ folks, working with business ( technical team and partners ) Work environment: (Required) • Excellent communication, • Choppy tenure, • Any project done outside of work (Data Science work) is also welcome., • If candidate isn’t local at this time, we are not interested in in reviewing those resumes at this time.Company DescriptionWorking with brand new state of the art security technologies and methodologies, remote work full time, great benefits, 401K.Working with brand new state of the art security technologies and methodologies, remote work full time, great benefits, 401K.

Job DescriptionWe're Topaz Labs, an AI tech company that builds software to solve imaging problems like denoising, super-resolution, and deconvolution with deep learning. Over 1M photographers and designers trust us with their work, including on teams at Google, Nvidia, NASA, and more. We've processed over 1 billion images, achieved 1000% revenue growth in the last 4 years, and we're only getting started. We’re looking for a Research Scientist to help us push the state-of-the-art in image and video enhancement. Your primary responsibility will be to explore and develop new deep learning models to solve inverse problems in imaging. You'll also evaluate customer feedback and image data to gauge performance and refine your models based on real-world usage.About us • Rocketship growth and opportunity for impact ($3M → $30M revenue in four years), • Over 1 million customers (including companies like Apple, NASA, Netflix) have used us for over 1 billion photos. Our tech has been covered by Fast Company, The Verge, Engadget, Mashable, BBC, and more, • World-class team that executes quickly, obsesses about the customer experience, and promotes from within, • Profitable company with infinite runwayAbout you, • PhD or equivalent industry experience, • Prior key contributor to significant deep learning projects for image enhancement or image processing, • Significant prior experience with CNNs, GANs, Diffusion, and other common computer vision network architectures, • 2 years of hands-on experience with TensorFlow or PyTorch, • Good understanding of common image processing algorithms, • Working knowledge of C/C++

Job DescriptionBenefits: • Competitive salary, • Flexible schedule Roles & Responsibilities : • Design, build, fine-tune, and deploy LLMs, transformer-based NLP models, and GenAI solutions for both batch and real-time/streaming contexts., • Own all major components of ML pipelines: data ingestion, cleaning, pre-processing (structured & unstructured), embedding, search & retrieval, prompt engineering, RAG (Retrieval-Augmented Generation)., • Collaborate closely with ML Engineers, MLOps, software engineering, product, compliance, legal etc., to move models from prototype to productionensuring reliability, scalability, monitoring, and maintainability., • Define and implement evaluation frameworks: accuracy, bias, fairness, hallucination, consistency, latency; run UAT, stress-tests, drift detection., • Optimize models and pipelines for performance, cost, and efficiency., • Ensure best practices in model development: version control, repeatability, documentation, governance, and ethical AI use., • Mentor more junior data scientists; help build team skills in NLP, GenAI practices, prompt engineering, fine-tuning., • Identify new use cases; prototype innovations in GenAI/NLP; keep up with latest research and open source developments, decide what to adopt. Must-Have Qualifications: • 10+ years of experience in data science / ML, with substantial work in NLP, LLMs, or Generative AI., • Deep hands-on experience in Python, using frameworks like PyTorch, TensorFlow, HuggingFace etc., • Proven track record building transformer/NLP / LLM models; experience with fine-tuning, prompt engineering., • Solid experience with information retrieval / search: keyword + semantic search, embeddings, vector databases., • Experience working in production / deploying models (batch and streaming), working with MLOps practices., • Strong algorithmic / statistical / mathematical fundamentals. Ability to reason about model behaviour, bias, uncertainty., • Good communicator: able to translate complex technical detail to business / non-technical stakeholders. Nice to Have: • Master's in Computer Science, Computational Linguistics, Statistics, Machine Learning or related field., • Experience with multimodal models (vision + text) or emerging LLMs and agent-based systems., • Experience with open source LLMs & toolkits; familiarity with LangChain or similar frameworks., • Prior experience in regulated environments (finance, risk, legal, compliance) with strong governance, privacy requirements. Work remote temporarily due to COVID-19.

Job Description Job Title: Junior Data Scientist Visa: Independent Visa candidates only Hybrid Required Qualifications • Bachelor’s degree in Data Science, Computer Science, Statistics, or related field., • 2–3 years of experience in data analysis, machine learning, or similar roles., • Proficiency in Python or R, and SQL., • Basic knowledge of machine learning techniques and statistics., • Familiarity with data visualization tools (e.g., Tableau, Power BI, matplotlib). Preferred Skills • Experience with Git and cloud platforms (AWS, Azure, or GCP)., • Internship or project experience in analytics or machine learning. Soft Skills • Strong problem-solving abilities and attention to detail., • Good communication and teamwork skills.Company DescriptionMagnus Technology Solutions provide quick orientation / training for professionals & placement for candidates having work authorization in USA. We work on #Selenium, #QA_Testing, #QA_Automation, #Manual_Testing #Dotnet, #java, #j2ee, #java_UI, #Angular, #React, #Python, #DevOps, #Salesforce, #Hadoop, #IOS, #Android, #RPA, #Mulesoft and any #Developer related #Technologies.Magnus Technology Solutions provide quick orientation / training for professionals & placement for candidates having work authorization in USA. We work on #Selenium, #QA_Testing, #QA_Automation, #Manual_Testing #Dotnet, #java, #j2ee, #java_UI, #Angular, #React, #Python, #DevOps, #Salesforce, #Hadoop, #IOS, #Android, #RPA, #Mulesoft and any #Developer related #Technologies.

Job DescriptionVaro is an entirely new kind of bank. All digital, mission-driven, FDIC insured and designed for the way our customers live their lives. A bank for all of us. Each member of the Data team plays an integral part of what we are building at Varo. We rely on advanced techniques in machine learning, cloud platforms and big data to drive decisions across the organization. If you are interested in working with an impressive team of Data pros who collaborate and challenge each other, and want to solve interesting problems to propel the company’s growth, apply now!What you'll be doing • Develop custom models and algorithms to apply to large datasets, as well as, processes for monitoring and analyzing their performance, • Mine and analyze data from different resources, and use predictive modeling to increase and optimize customer experiences, customer acquisition, underwriting and other business outcomes, • Assess the effectiveness and accuracy of new data sources and data gathering techniques, • Understand and apply proper risk framework to your analysis and modeling., • Work with stakeholders throughout the organization to identify opportunities for leveraging data to drive business decisions, • Collaborate cross functionally to implement models and monitor outcomesYou'll bring the following required skills and experiences, • 7+ years of experience in Analytics, Data Science or Data Engineering as an individual contributor, • An advanced degree in a quantitative field - computer science, engineering, statistics, operations research, economics, etc, • Credit and / or Fraud Risk modeling experience in consumer finance is nice to have, • Strong problem solving skills with an emphasis on translating real-life problems into a concrete model development strategy. Blend academic rigor with a sense of pragmatism for rapidly prototyping and delivering solutions, • Experienced in using Python for analysis and modeling, • Experience applying a wide range of statistical techniques to large data sets, and understanding their real-world advantages/drawbacks, • Experience using web services (AWS, GCP), and distributed data/computing tools (Spark, Map/Reduce, Hadoop, Hive, etc.), • Excellent cross-functional communication skills

Job DescriptionBenefits: • HYBRID, • Competitive salary, • Opportunity for advancement Work Arrangement • Hybrid work model: primarily remote within the DallasFort Worth area., • Occasional on-site presence required for meetings, training, or business needs., • Limited business travel may be required. Roles & Responsibilities . 6+ years of experience in Machine Learning and Data Science. Strong understanding of Generative AI, Retrieval Augmented Generation, Agentic Workflow, Statistical methods, data structures, and algorithms. Strong programming skills in Python; experience with Machine Learning libraries and Generative AI frameworks (e.g., Pandas, NumPy, Matplotlib, Seaborn, TensorFlow, PyTorch, scikit-learn, LangChain) and LLMs. Experience developing and deploying AI solutions on cloud platforms (e.g., AWS, Azure, or GCP). Experience in building Asynchronous Python APIs. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau. Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for deploying AI solutions. Proven experience in developing and deploying machine learning models in a production environment. Experience working with large datasets and performing data analysis Required Qualifications Education • Bachelor's degree in Mathematics, Computer/Data Science, Information Technology, or a related field, or equivalent experience. Experience • Advanced experience in data science, machine learning, AI, or optimization projects., • Proficiency in Python and SQL., • Strong understanding of statistical methods, experimental design, and model validation., • Experience with data pipelines and relevant programming libraries (e.g., Pandas, NumPy, Scikit-learn, XGBoost, TensorFlow, Pyspark)., • Familiarity with data visualization tools (e.g., Tableau, Plotly, Streamlit). Preferred Experience • Experience with AWS cloud services (e.g., SageMaker, Lambda, Glue, EMR)., • Exposure to specialized analytics areas such as simulation, graph analytics, or video analytics. Skills & Abilities • Ability to independently manage and deliver on complex projects., • Strong problem-solving and critical thinking skills., • Effective communication skills for both technical and executive audiences., • Ability to adapt quickly to changing priorities and new technologies., • Strong interpersonal and collaboration skills. .....

Job Description Position Summary: We are seeking a motivated Data Scientist to research, develop, and enhance machine learning and deep learning algorithms that drive innovative healthcare solutions. This role involves maintaining high data quality standards, collaborating with clinical and business partners to understand their needs, and translating advanced research into practical applications. The ideal candidate will assist in building and improving deep learning frameworks, manage projects independently, and work effectively both individually and within cross-functional teams. Staying current with emerging technologies and demonstrating strong communication, attention to detail, and persistence are essential for success in this role. Essential Duties and Responsibilities: • Research, develop, and enhance machine learning and deep learning algorithms and frameworks for computer vision applications, translating cutting-edge research into practical healthcare solutions., • Implement and optimize deployment pipelines for trained models to enable efficient, scalable, and hardware-optimized inference., • Apply model optimization techniques to reduce computational overhead while preserving accuracy., • Maintain data quality and integrity across the data lifecycle to support robust algorithm development and model training., • Collaborate with clinical partners and internal stakeholders to understand needs and deliver AI solutions that improve model performance., • Assist in writing deep learning framework templates, identifying improvement areas, and implementing new model architectures., • Manage projects independently and contribute effectively as part of a team, ensuring reproducible analyses, clear documentation, and knowledge sharing., • Stay updated with the latest data science methods, technologies, and industry trends., • Strong foundation in state-of-the-art deep learning architectures (e.g., vision transformers) for computer vision tasks including image classification, object detection, and semantic segmentation., • Proficiency in deep learning libraries and frameworks, including PyTorch and TensorFlow., • Proficiency in C++ regarding object-oriented programming, data structure and performance optimization technique., • Solid knowledge of model optimization techniques, such as pruning, quantization, mixed-precision inference, and other performance-enhancing strategies., • Solid knowledge of model deployment tools, including ONNX, LibTorch, and TensorRT., • Strong grasp of model evaluation metrics, benchmarking, and best practices for computer vision model validation., • Self-driven with the ability to deliver on ambiguous projects with incomplete data., • Experience and knowledge in healthcare domain with successful outcomes. Prolonged periods of sitting at a desk and working on a computer. Travel: N/A Equal Employment Opportunity: Spectral MD, Inc. is an equal opportunity and affirmative action employer. All applicants will be considered for employment without regard to race, color, ancestry, national origin, sex, gender, sexual orientation, marital status, religion, age, disability, gender identity, results of genetic testing, protected veteran status, or any other characteristic protected by applicable federal, state or local laws.

Job Description At Pieces, one of our core value statements is that our customer’s mission is a sacred mission… and it's a hard mission. Our hope is to apply advanced AI to make the work of our customers – patient care – easier in as many ways as possible. We use cutting-edge approaches in AI such as agentic AI with clinician-in-the-loop, to help hospitals and healthcare providers reduce documentation and administrative burden, improve communication efficiency, capture revenue, and improve patient outcomes. Responsibilities As an Applied AI Scientist, you will be pivotal in advancing the responsible AI development, deployment, and optimization of our healthcare AI products. The role demands full-stack AI responsibilities and a proactive collaboration with various teams to develop and manage solutions that incorporate a holistic approach to AI system architecture, key generative AI tools, effective data representation, advanced modeling, AI evaluation, adversarial AI strategies, clinical knowledge graphs, and clinician-in-the-loop AI-user interaction. You'll play a vital role in ensuring that our AI systems enhance outcomes for both hospital systems and patients, and uphold our commitment to responsible innovation in healthcare. Duties and responsibilities include but not limited to: * Develop the AI evaluation modules under the large language model operations (LLMOps), which includes the components of LLM observability, benchmark datasets, standardization of metrics, evaluation of complex LLM workflow, knowledge graph, etc * Implement strategies of AI safety for adversarial detection AI, comprehensive model evaluation, and error analysis, incorporating human feedback for continuous AI model improvement * Maintain and continuously improve existing data models and AI Engine pipelines, including monitoring performance, resolving production issues, optimizing for scalability, and ensuring robust dataflows across the AI/ML and application stack. * Apply LLM observability tools, such as LangFuse, Arize Phoenix, Braintrust, etc, for LLM traces, latency and cost awareness, evaluation, and prompt management/deployment. * Develop data pipelines in AI engine to support a generic data store and data representation, including a meta-data layer for clinical semantics and a vector database for downstream applications * Develop generative and predictive AI modules and necessary data transformation modules in AI engine alongside agentic AI systems * Support agentic AI systems development using LangGraph and/or other agentic AI frameworks for the use cases such as AI assistants in both internal applications (e.g. SafeRead) and external ones (e.g. SmarterNotes) * Collaborate with clinical domain experts and product management teams to translate clinical guidelines into AI modules, ensuring that the developed products align with clinical needs and user requirements. * Stay updated with the latest AI advancements in the generative AI era, integrating new knowledge into practical applications and contributing to the AI community through professional engagements. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Requirements We’re looking for an Applied AI Scientist who’s passionate about using technology to help the most vulnerable. You’re someone who believes the right data can help build better one-to-one relationships with communities in need of extra support. You have expertise in the following areas: * Bachelor, Master's or Ph.D. in Computer Science, Data Science, Physics, Mathematics, Engineering, Informatics, or a related field * 3+ years of experience in data analytics and statistical/ML/NLP modeling, with a focus on healthcare applications * Proven experience with cloud infrastructure and services, particularly in the deployment of AI/ML models * Expertise in programming with Python and familiarity with AI/ML tools and frameworks * Familiarity with vibe coding tools, such as Claude Code, Codex, Cursor, Replit, etc * Demonstrated ability in the development and management of large-scale AI systems * Proficiency in cloud services (AWS, Azure) and familiarity with EKS clusters, Docker, Kubernetes, and MLOps practices * Strong background in generative AI, NLP, machine learning, and data science with a passion for innovation in healthcare AI * Exceptional problem-solving abilities and a commitment to quality and ethical AI practices * Excellent communication skills, capable of translating complex technical concepts to diverse stakeholders * Leadership and project management skills, with an ability to drive projects to completion in a fast-paced environment We offer competitive salaries as well as the following benefits: * Shared premiums: medical, dental and vision, plus access to FSA and HSA * 401K and life insurance * Flexible vacation and holiday policies * Flexible work hours, with work-from-home options * Paid maternity/paternity leave * A comprehensive tech setup

Job Description Note: Only on W2 Must be local to either Cary, NC or Irving, TX Client: Caterpillar Education: • Bachelors or Masters are required Qualifications: • 5+ years of experience are required Top Skills: • Proficiency in Python, SQL, and data science libraries (Pandas, Scikit-learn, TensorFlow), • Strong foundation in statistics, probability, and machine learning, • Familiarity with cloud platforms (Azure, AWS, Snowflake) and data modeling, • Excellent communication skills to explain technical concepts to non-technical stakeholders Job Duties: • A Data Scientist is responsible for analyzing large volumes of structured and unstructured data to extract actionable insights, build predictive models, and support data-driven decision-making., • This role blends statistical expertise, programming skills, and business acumen to solve complex problems and drive innovation., • Data Collection & Preparation: Gather, clean, and validate data from various sources to ensure quality and usability, • Exploratory Data Analysis: Identify trends, anomalies, and patterns in large datasets, • Model Development: Design and implement machine learning models (e.g., regression, classification, clustering, NLP) to support forecasting and decision-making, • Data Visualization: Create dashboards and reports using tools like Power BI, etc., to communicate findings, • Automation & Optimization: Develop scripts and tools to automate data processing and model deployment, • Collaboration: Work cross-functionally with product, engineering, and business teams to align data initiatives with strategic goals, • Research & Innovation: Stay current with emerging technologies and methodologies in data science and apply them to business challenges

Job Description EnSafe is accepting applications for a Senior Technical Professional to join our team in one of our primary office locations, which include: Charleston, South Carolina; Houston, Texas; Jacksonville, Florida; Pensacola, Florida; Huntsville, Alabama; and Memphis, Tennessee. Candidates must be willing to work at an EnSafe Office location listed above. Relocation assistance is available to meet this expectation. What We Are Looking for: A Senior Technical Professional who is a problem-solver and environmental strategist who can provide senior technical support to multiple project teams. An Engineer/Geologist/Environmental Scientist who enjoys working on various projects in an environment that fosters creativity, collaboration at all levels, and professional growth. EnSafe empowers staff to practice our profession passionately and without limitations. What You Will Be Doing: • Providing senior technical support to project teams working across multiple offices nationwide, including strategic problem-solving, regulatory support, and meeting with clients and subcontractors., • Overseeing the quality assurance/quality control of deliverables for projects and tasks managed by others., • Reviewing Work Plans and/or Sampling and Analysis Plans, as well as other project deliverables (e.g., Remedial Investigations, Feasibility Studies, Proposed Plans, Records of Decisions, Five-Year Reviews) developed by project teams., • Preparing high-level technical reports, as needed, to support complex strategic or regulatory issues., • Working with dynamic project teams and mentoring junior staff., • Maintaining and developing relationships with existing EnSafe clients through excellent quality of work, responsiveness, and service., • Project sites will include Superfund sites, large, complex federal facilities/military installations, and commercial/industrial properties. What You Will Need: • U.S. Citizenship is required., • BS in Geology, Engineering, Biology, Chemistry, Environmental Science, or related field., • Minimum of 12 years of experience., • Knowledge and experience navigating projects under RCRA and CERCLA frameworks., • Experience preparing Uniform Federal Policy Sampling and Analysis Plans., • Experience working on projects under the Department of Defense., • Previous experience executing projects under federal assessment, remediation, and munitions programs., • Previous experience with PFAS investigation, fate and transport, and response actions., • Knowledge and understanding of chemistry/data validation, statistics, modeling, and risk assessment, sufficient to coordinate with specialty teams/subject matter experts on a routine basis. About Us: EnSafe began as a two-person firm in 1980, navigating complex regulatory compliance issues on behalf of our clients. We nurture our people with growth and development opportunities. We build enduring, trustful relationships with each of our clients, with a focus on high ethical, quality, and safety standards. We maintain and enrich this reputation by attracting high-quality people and retaining them for the long term. At EnSafe, we are dedicated to fostering a diverse and authentic workplace, so if you’re excited about this role but your experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles at our company. EnSafe is committed to being an EEO employer and all qualified candidates will receive consideration without regard to race, color, religion, national origin, citizenship, age (except for bona fide occupational qualifications), sex, disability, sexual orientation, gender identity, marital status, military or veteran status, any other status protected by federal, state, or local law, or association with a person on the basis on one or more of the foregoing. Check us out on the web at #LIMJ

Hands-on expertise in graph data analysis, including anomaly detection and distribution pattern extraction. Proficiency in Python and common data science/AI libraries. Analyze graph-structured data to detect anomalies, extract probabilistic patterns, and support graph-based intelligence.

Key Responsibilities - Statistical Failure Analysis: Identify patterns in AI agent failures across task components (prompts, rubrics, templates, file types, tags) - Root Cause Analysis: Determine whether failures stem from task design, rubric clarity, file complexity, or agent limitations -

Provide technical leadership and mentorship to junior data scientists; guide hands-on work in context engineering, model tuning, and advanced data analysis. Proficient in Python and its data science ecosystem; experienced in building solutions on data platforms like Databricks or Microsoft Fabric an

What You’ll Do** - Analyze large, complex datasets to uncover patterns, develop insights, and inform modeling direction - Build predictive models, statistical analyses, and machine learning pipelines across tabular, time-series, NLP, or multimodal data - Design and implement robust validation stra

Key Responsibilities - Statistical Failure Analysis: Identify patterns in AI agent failures across task components (prompts, rubrics, templates, file types, tags) - Root Cause Analysis: Determine whether failures stem from task design, rubric clarity, file complexity, or agent limitations -

What You’ll Do** - Analyze large, complex datasets to uncover patterns, develop insights, and inform modeling direction - Build predictive models, statistical analyses, and machine learning pipelines across tabular, time-series, NLP, or multimodal data - Design and implement robust validation stra

Coordinates with Data Engineers to build data environments providing data identified by Data Analysts, Data Integrators, Knowledge Managers, and Intel Analysts. Defines company data assets (data models), spark, sparkSQL, and hiveSQL jobs to populate data models. Data Scientist Job Duties:

What You’ll Do** - Analyze large, complex datasets to uncover patterns, develop insights, and inform modeling direction - Build predictive models, statistical analyses, and machine learning pipelines across tabular, time-series, NLP, or multimodal data - Design and implement robust validation stra

Coordinates with Data Engineers to build data environments providing data identified by Data Analysts, Data Integrators, Knowledge Managers, and Intel Analysts. Defines company data assets (data models), spark, sparkSQL, and hiveSQL jobs to populate data models. Data Scientist Job Duties:

What You’ll Do** - Analyze large, complex datasets to uncover patterns, develop insights, and inform modeling direction - Build predictive models, statistical analyses, and machine learning pipelines across tabular, time-series, NLP, or multimodal data - Design and implement robust validation stra

Coordinates with Data Engineers to build data environments providing data identified by Data Analysts, Data Integrators, Knowledge Managers, and Intel Analysts. Defines company data assets (data models), spark, sparkSQL, and hiveSQL jobs to populate data models. Data Scientist Job Duties:

Key Responsibilities - Statistical Failure Analysis: Identify patterns in AI agent failures across task components (prompts, rubrics, templates, file types, tags) - Root Cause Analysis: Determine whether failures stem from task design, rubric clarity, file complexity, or agent limitations -

Coordinates with Data Engineers to build data environments providing data identified by Data Analysts, Data Integrators, Knowledge Managers, and Intel Analysts. Defines company data assets (data models), spark, sparkSQL, and hiveSQL jobs to populate data models. Data Scientist Job Duties:

What You’ll Do** - Analyze large, complex datasets to uncover patterns, develop insights, and inform modeling direction - Build predictive models, statistical analyses, and machine learning pipelines across tabular, time-series, NLP, or multimodal data - Design and implement robust validation stra

Coordinates with Data Engineers to build data environments providing data identified by Data Analysts, Data Integrators, Knowledge Managers, and Intel Analysts. Defines company data assets (data models), spark, sparkSQL, and hiveSQL jobs to populate data models. Data Scientist Job Duties:

Coordinates with Data Engineers to build data environments providing data identified by Data Analysts, Data Integrators, Knowledge Managers, and Intel Analysts. Defines company data assets (data models), spark, sparkSQL, and hiveSQL jobs to populate data models. Data Scientist Job Duties:

Our data scientists use advanced analytics to understand customer preferences, forecast trends that shape the industry and optimize our business. Data analytics skills and experience analyzing both experimental and observational data sets. At Hershey, data isn't just about numbers-it's about creatin

Coordinates with Data Engineers to build data environments providing data identified by Data Analysts, Data Integrators, Knowledge Managers, and Intel Analysts. Defines company data assets (data models), spark, sparkSQL, and hiveSQL jobs to populate data models. Data Scientist Job Duties:

Provides expert technical guidance and integrates with a team of data scientists, applied AI scientists, engineers, and analysts responsible for multiple technologies. Acts as technical lead for enterprise data management platform implementation for CRM redesign. Applies expert business skills and c

Coordinates with Data Engineers to build data environments providing data identified by Data Analysts, Data Integrators, Knowledge Managers, and Intel Analysts. Defines company data assets (data models), spark, sparkSQL, and hiveSQL jobs to populate data models. Data Scientist Job Duties:

Build, maintain, and optimize data pipelines and data models {including work with Data Build Tool (DBT)}. Hands-on experience with Data Build Tool (DBT) for data modeling. Someone who can blend technical rigor with business understanding—comfortable working end-to-end across data engineering, anal