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We are hiring for Data Scientist. Title : Data Scientist Work Arrangement: Hybrid Location : Newark NJ (3 days required to work from officer / Per week) Required Skills : Data Scientist, Agent-to-Agent (A2A) & Model Context Protocol (MCP) Please email me your resume at Job Description: Job Description Are you interested in building capabilities that enable the organization with innovation, speed, agility, scalability, and efficiency The Global Technology team takes great pride in our culture where digital transformation is built into our DNA! As a Data Scientist supporting client Advisors in the U.S. Businesses (USB) Service, Data and Technology organization, you will partner with our diverse team of Engineers, Economists, Computer Scientists, Mathematicians, Physicists, Statisticians and Actuaries tasked with mining our industry-leading internal data to design, build, and deploy production-grade AI capabilities for our businesses. Here is what you can expect in a typical day: Responsible for the hands-on design and development of production-grade GenAI and Agentic solutions comprising the portfolio developed by the Data Science Lead and the technical requirements specified. Perform hands-on context engineering, agent design, model integration, and end-to-end AI system development. Design and build AI agent harnesses, orchestration frameworks, and context engineering pipelines; develop and integrate Model Context Protocol (MCP) servers to expose tools, data sources, and enterprise APIs to AI agents in a standardized, secure manner; and implement Agent-to-Agent (A2A) communication patterns and multi-agent architectures to solve complex, multi-step business problems. Write production-level code and partner with machine learning engineers and platform teams to deliver AI solutions from development through production following the full AI lifecycle. Continuously research new methods for problem solution, including new algorithms, agentic frameworks, context management techniques, and AI application patterns. The Skills and expertise you bring: • Advanced degree in Mathematics, Statistics, Engineering, Econometrics, Physics, Computer Science, Actuarial, Data Science, or comparable quantitative disciplines, • Working on complex problems in which analysis of situations or data requires an in-depth evaluation of various factors. Exercises judgment within broadly defined practices and policies in selecting methods, techniques and evaluation criteria for obtaining results. Applied experience with several of the following: • AI Engineering & Production AI Lifecycle: Ability to design, build, and deliver AI systems end-to-end in a production environment. Deep understanding of the AI lifecycle — from problem framing and data preparation through model development, evaluation, deployment, monitoring, and continuous improvement. Experience with CI/CD for AI, model versioning, observability, and responsible AI practices., • Generative AI, Agentic & Context Engineering: Expertise in modern Generative AI and NLP technologies including LLMs, RAG, LangChain, LangGraph, vector databases, etc. Skilled in context engineering — prompt engineering, dynamic context construction, context window management, and structured output design. Experience building AI agent harnesses and orchestration frameworks including scaffolding, tool registries, and evaluation loops. Hands-on experience designing MCP servers to expose enterprise tools and APIs to AI agents, and implementing Agent-to-Agent (A2A) communication patterns and multi-agent architectures to solve complex, multi-step business problems. • Machine Learning: Understanding of machine learning theory, including the mathematics underlying machine learning algorithms. Expertise in the application of machine learning theory to building, training, testing, interpreting and monitoring machine learning models, • Data Acquisition and Transformation: Acquiring data from disparate data sources using API’s and SQL. Transform data using SQL and Python. Visualizing data using a diverse tool set including but not limited to Python., • AWS DevOps: Experience in the project development life cycle in an AWS environment. Familiar with development, QA, staging and production deployment stages., • Programming Languages: Python, SQL Thanks and Regards, Ankit Grover Sr. Executive - TA Iris Software 200 Metroplex Drive, Suite #300, Edison, NJ 08817 Email : Phone : 973-370-7012

Contract to hire position with a major financial firm. This position is hybrid to Newark, NJ As a Data Scientist on the Data Science team, you will partner with our diverse team of Engineers, Economists, Computer Scientists, Mathematicians, Physicists, Statisticians and Actuaries tasked with mining our industry-leading internal data to develop new analytics capabilities for our businesses. The role requires a rare combination of sophisticated analytical expertise; business acumen; strategic mindset; client relationship skills, problem solving; and a passion for generating business impact. This is an exciting opportunity to be a part of a strategic initiative that is evolving and growing over time! In addition to applied experience, you will bring excellent problem solving, communication and teamwork skills, along with agile ways of working, strong business insight, an inclusive leadership demeanor and a continuous learning focus to all that you do. Here is what you can expect in a typical day: • Responsible for the hands-on development of sophisticated data science solutions comprising the portfolio developed by the Lead Data Scientist and Actuaries and the technical requirements specified by the Lead Data Scientist and Actuaries. • Perform hands-on data analysis, model development, model training, model testing, model deployment. • Continuously research new methods for problem solution, including new algorithms, modeling techniques, and data analytics techniques. • Write production-level code and partner with machine learning engineers to push development code into production. • Partner with machine learning engineers to productionized machine learning models. Partner with data engineers to build data pipelines. Partner with software engineers to integrate solutions with business platforms. • Work closely with the business and data science lead to recommend and develop models for GI financial underwriting, medical underwriting, marketing analytics and other business use cases. • Manage external vendors in the execution of the data science development process. The Skills and expertise you bring: • Advanced degree (Masters, Ph.D.) in Mathematics, Statistics, Engineering, Econometrics, Physics, Computer Science, Actuarial, Data Science, or comparable quantitative disciplines. • Working on complex problems in which analysis of situations or data requires an in[1]depth evaluation of various factors. Exercises judgment within broadly defined practices and policies in selecting methods, techniques, and evaluation criteria for obtaining results. • Knowledge of business concepts, tools and processes that are needed for making sound decisions in the context of the company's business. Create and test hypotheses for customer engagement and wellness programs. • Experience in research, designing experiments (ex: A/B testing), working with claims and customer experience data. An insurance actuary background is preferred but not required. • Ability to learn creative skills and knowledge on an on-going basis through self[1]initiative and solving challenges., • Excellent problem solving, communication and collaboration skills. Applied experience with several of the following: • Data Acquisition and Transformation: Acquiring data from disparate data sources using API's, SQL and NoSQL. Transform data using SQL, NoSQL, and Python. Visualizing data using a diverse tool set including but not limited to Python and R. • Database Management System: Knowledge of how databases are structured and function in order to use them e8iciently may include multiple data environments, cloud/AWS, primary and foreign key relationships, table design, database schemas, etc. o Knowledge of how to work with data from (do not build) o SQL skills (relational) - CORE / Initial Proficiency o Unstructured (NoSQL) o Graph / ontology (DB Graph) • Model Deployment: Understanding of: MDLC (Model Development Life Cycle), CI/CD/CT pipelines (using tools like Jenkins, CloudBees, Harness etc.), A/B testing. Pipeline frameworks like MLFlow, AWS SageMaker pipeline etc. model and data versioning. • Statistics and Computing: Exceptional understanding of: Calculus, Multivariable Calculus, Linear Algebra, Di8erential Equations, Probability, Statistics, Applied Probability, Applied Statistics, Computer Science (Programming Methodologies), and Cloud. Knowledge of statistical techniques such as the use of descriptive, inferential, bayesian statistics, time series analysis etc. to extract business insights and experimentation to solve business problems • Data Wrangling: Preparing data for further analysis; Redefining and mapping raw data to generate insights; Processing of large datasets (structured, unstructured). • Machine Learning: Understanding of machine learning theory, including the mathematics underlying machine learning algorithms. Expertise in the application of machine learning theory to building, training, testing, and monitoring machine learning models. Understanding and expertise in NLP (natural language processing). • Programming Languages: Python, R, SQL, Java or Scala, SQL, Cypher

Job Title: Data Scientist Duration: 6 Months to hire Location: Newark, NJ Job description: As a Data Scientist supporting U.S. Businesses (USB) Service, Data and Technology organization, you will partner with our diverse team of Engineers, Economists, Computer Scientists, Mathematicians, Physicists, Statisticians and Actuaries tasked with mining our industry-leading internal data to design, build, and deploy production-grade AI capabilities for our businesses. The role requires a rare combination of sophisticated AI engineering expertise; business acumen; strategic mindset; client relationship skills, problem solving; and a passion for generating business impact. This is an exciting opportunity to be a part of a strategic initiative that is evolving and growing over time! In addition to applied experience, you will bring excellent problem solving, communication and teamwork skills, along with agile ways of working, strong business insight, an inclusive leadership demeanor and a continuous learning focus to all that you do. This role is based in our office in Newark, NJ. Our organization follows a hybrid work structure where employees can work remotely and from the office, as needed, based on demands of specific tasks or personal work preferences. This position is hybrid and requires your on-site presence on a reoccurring weekly basis at least 3 days per week. Here is what you can expect in a typical day: • Responsible for the hands-on design and development of production-grade GenAI and Agentic solutions comprising the portfolio developed by the Data Science Lead and the technical requirements specified. Perform hands-on context engineering, agent design, model integration, and end-to-end AI system development., • Design and build AI agent harnesses, orchestration frameworks, and context engineering pipelines; develop and integrate Model Context Protocol (MCP) servers to expose tools, data sources, and enterprise APIs to AI agents in a standardized, secure manner; and implement Agent-to-Agent (A2A) communication patterns and multi-agent architectures to solve complex, multi-step business problems., • Write production-level code and partner with machine learning engineers and platform teams to deliver AI solutions from development through production following the full AI lifecycle., • Continuously research new methods for problem solution, including new algorithms, agentic frameworks, context management techniques, and AI application patterns., • Partner with machine learning engineers to productionize AI solutions. Partner with data engineers to build data pipelines. Partner with software engineers to integrate solutions with business platforms. The Skills and expertise you bring: • Advanced degree (Masters, Ph.D.) in Mathematics, Statistics, Engineering, Econometrics, Physics, Computer Science, Actuarial, Data Science, or comparable quantitative disciplines, • Working on complex problems in which analysis of situations or data requires an in-depth evaluation of various factors. Exercises judgment within broadly defined practices and policies in selecting methods, techniques and evaluation criteria for obtaining results., • Ability to learn new skills and knowledge on an ongoing basis through self-initiative and seeking challenges, • Excellent problem solving, communication and collaboration skills Applied experience with several of the following: • AI Engineering & Production AI Lifecycle: Ability to design, build, and deliver AI systems end-to-end in a production environment. Deep understanding of the AI lifecycle — from problem framing and data preparation through model development, evaluation, deployment, monitoring, and continuous improvement. Experience with CI/CD for AI, model versioning, observability, and responsible AI practices., • Generative AI, Agentic & Context Engineering: Expertise in modern Generative AI and NLP technologies including LLMs, RAG, LangChain, LangGraph, vector databases, etc. Skilled in context engineering — prompt engineering, dynamic context construction, context window management, and structured output design. Experience building AI agent harnesses and orchestration frameworks including scaffolding, tool registries, and evaluation loops. Hands-on experience designing MCP servers to expose enterprise tools and APIs to AI agents, and implementing Agent-to-Agent (A2A) communication patterns and multi-agent architectures to solve complex, multi-step business problems., • Machine Learning: Understanding of machine learning theory, including the mathematics underlying machine learning algorithms. Expertise in the application of machine learning theory to building, training, testing, interpreting and monitoring machine learning models, • Data Acquisition and Transformation: Acquiring data from disparate data sources using API's and SQL. Transform data using SQL and Python. Visualizing data using a diverse tool set including but not limited to Python., • Database Management System: Knowledge of how databases are structured and function in order to use them efficiently. May include multiple data environments, cloud/AWS, primary and foreign key relationships, table design, database schemas, etc., • Data Wrangling: Preparing data for further analysis; Redefining and mapping raw data to generate insights; Processing of large datasets (structured, unstructured)., • AWS DevOps: Experience in the project development life cycle in an AWS environment. Familiar with development, QA, staging and production deployment stages., • Programming Languages: Python, SQL

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence company building technology that helps users organize data, discover the truth, and act on it with confidence. Our AI-powered, cloud platform, RelativityOne, transforms massive volumes of complex information into actionable insights for litigation, investigations, regulatory inquiries, data breach responses, and other highstakes legal work where accuracy, trust, and defensibility are essential. Relativity aiR is redefining document review through agentic AI systems that reason, cite their decisions, and scale across millions of documents. These systems automate complex legal workflows while keeping humans in the loop, enabling legal professionals to focus on what matters most. WHAT WE DO At Relativity, we are building a worldclass Applied Science organization focused on pushing the boundaries of intelligent systems in one of the most demanding and consequential domains: the legal system. Applied Science Team The Applied Science team sits at the core of Relativity's AI development. We are responsible for designing, validating, and operating the intelligent systems behind Relativity aiR. Our work goes far beyond simple model integrations. We build agentic systems that reason over documents, validate decisions statistically, remain auditable and defensible, and operate reliably at massive scale. Trust, reliability, and responsibility are foundational to everything we build. Our team values curiosity, experimentation, rigor, and collaboration. We move quickly, validate assumptions with evidence, and simplify aggressively to deliver systems that are safe, reliable, and impactful in production. Job Description and Requirements ABOUT THE ROLE As a Principal Applied Scientist, Reliability, you will lead the design and validation of intelligent systems that customers can trust in highstakes legal workflows. You will operate endtoend: understanding the problem space, designing solutions, validating them statistically, and bringing them to production in partnership with engineering, product, and customerfacing teams. This role is ideal for an experienced applied scientist who thrives at the intersection of modeling, experimentation, and realworld system reliability, and who is motivated by building AI systems that are not only powerful, but also defensible, interpretable, and safe by design. WHAT YOU'LL DO • Write productionquality code that solves real customer problems and scales cleanly, with systems designed to be easy to ship, operate, and maintain, • Collaborate closely with fellow Applied Scientists as well as Engineers, Product Managers, Designers, and Customers, • Design and execute statistically sound experiments and automate them into reusable benchmarks and evaluation frameworks, • Rapidly prototype AI and MLpowered solutions and mature them into reliable, scalable production models, • Select the appropriate modeling approach for each problem, ranging from classical machine learning techniques to frontier large language models, • Validate model behavior rigorously using evidence, metrics, and experimentation, remaining open to changing course when the data demands it, • Contribute to building intelligent systems that reason, cite their decisions, and operate defensibly at scale, • Help push the boundaries of agentic AI while ensuring systems remain auditable, reliable, and responsible WHAT WE'RE LOOKING FOR • 8+ years of professional experience in applied science, machine learning, or a closely related field, • Master's or Ph.D. in Computer Science, Statistics, Applied Mathematics, or a related quantitative discipline, or equivalent professional experience, • Proven ability to move quickly from prototype to production, simplifying complex ideas into robust systems, • Experience reading, validating, and applying research with a healthy level of skepticism, • Experience across a wide range of modeling techniques, from classical machine learning to largescale generative models, • Familiarity with modern MLOps tooling and practices, including containers, workflow orchestration, deployment patterns, telemetry, and experimentation systems, • Strong Python programming skills and experience with common data and ML libraries such as numpy, PyTorch, scikitlearn, and PySpark, • Strong communication skills, with the ability to explain complex technical concepts clearly to both technical and nontechnical audiences, • Endtoend ownership mindset, with the ability to understand new problem spaces, design solutions, and bring them to market alongside engineering, product, and support partners, • A collaborative, curious, and adaptable approach, with comfort leading, questioning assumptions, and learning from failure WHY WE COULD BE A GREAT FIT HighImpact Problems • Competitive compensation, health and retirement programs, discretionary time off (DTO), parental leave for primary and secondary caregivers, companywide breaks, wellness resources, and an equity program. Relativity is committed to competitive, fair, and equitable compensation practices. This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives. The expected salary range for this role is between following values: $224,000 and $336,000 The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position. Required Skills: Algorithms, Data Analysis, Machine Learning (ML), Natural Language, Python (Programming Language), Reinforcement Learning, Researching, Scientific Writing, Statistical Models, Technical Leadership

Company Overview KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem. Virtually every electronic device in the world is produced using our technologies. No laptop, smartphone, wearable device, voice-controlled gadget, flexible screen, VR device or smart car would have made it into your hands without us. KLA invents systems and solutions for the manufacturing of wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays. The innovative ideas and devices that are advancing humanity all begin with inspiration, research and development. KLA focuses more than average on innovation and we invest 15% of sales back into R&D. Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the world's leading technology providers to accelerate the delivery of tomorrow's electronic devices. Life here is exciting and our teams thrive on tackling really hard problems. There is never a dull moment with us. Group/Division With over 40 years of semiconductor process control experience, chipmakers around the globe rely on KLA to ensure that their fabs ramp next-generation devices to volume production quickly and cost-effectively. Enabling the movement towards advanced chip design, KLA's Global Products Group (GPG), which is responsible for creating all of KLA's metrology and inspection products, is looking for the best and the brightest research scientist, software engineers, application development engineers, and senior product technology process engineers. The Surfscan group includes a team of engineers, technology development, apps engineers and product marketing focused on technology that enables wafer, IC and equipment manufacturers to develop, qualify and monitor their process tools. Defects and process non-uniformities detected on Surfscan equipment allow for early identification of yield excursions. The flagship Surfscan products include the SPx platforms for wafer surface quality and wafer defect inspection tools and systems for inspection of polished wafers, epi wafers and engineered substrates during the wafer fabrication process. Job Description/Preferred Qualifications Summary KLA seeks a technology leader to lead strategic marketing for the Surfscan portfolio, collaborating closely with R&D and customers. This new role combines strategic marketing with advanced technology development, focusing on guiding long-term R&D, technology roadmaps, and future product architectures. This role offers a unique opportunity to shape the future of semiconductor process control and position the successful candidate for potential advancement into a Business Unit Manager role. The Surfscan group encompasses a diverse and innovative set of technologies, including: * Unpatterned Wafer Inspection: Industry-leading platforms such as the SPx series for surface defect detection and quality assurance. * Shape Metrology: Advanced solutions for measuring wafer shape across both patterned and unpatterned substrates. * Chemical Metrology: Precision tools for monitoring and controlling electroplating, etch, and clean chemistries. * Specialty Instruments: Inspection and metrology systems tailored for niche substrates and benchtop applications in industrial and academic settings. The group is powered by a multidisciplinary team of physicists, chemists, engineers, data scientists, and business professionals, all working together to deliver breakthrough solutions to the semiconductor ecosystem. Key Responsibilities The Head of Strategic Marketing will serve as a critical thought leader and business driver, responsible for: * Defining and executing roadmaps across Surfscan portfolio * Identifying, assessing, and championing advanced technologies (optical, sensor, computational, algorithmic, materials, and subsystem innovations) for integration into future products to address inflections. * Working with internal research organizations, external partners, and university collaborators to shape the next decade of product lines * Driving market adoption of next-generation solutions through deep customer engagement and ecosystem insight. * Translating complex technical capabilities into compelling value propositions for global customers. * Partnering with product development, applications, sales, and executive leadership to align strategy with execution. * Leading cross-functional initiatives that shape product positioning, pricing, go-to-market strategy, and long-term portfolio planning. * Acting as a player-coach-mentoring a high-performing team while remaining hands-on in strategic initiatives. Ideal Candidate Profile The successful candidate will bring: * Proven Leadership: A track record of deep technical experience in semiconductor equipment design and development; Extensive understanding of semiconductor process technologies and how inflections impact equipment designs. * Commercial Acumen: Demonstrated ability to launch and scale innovative products in inspection, shape, or chemical metrology. * Industry Expertise: Deep familiarity with the semiconductor manufacturing landscape and a strong network across the ecosystem. * Technical Credibility: Ability to engage with engineering and scientific leaders, and synthesize complex technologies into business impact. * Executive Presence: Strong communication, influence, and decision-making skills, with the ability to represent Surfscan at the highest levels. This role is ideal for a strategic leader who thrives at the intersection of technology, business, and customer impact-and who aspires to broader general product portfolio management responsibilities in the future. Minimum Qualifications * Doctorate (Academic) and a minimum of 10 years of relevant experience OR * Master's Level Degree and a minimum of 13 years of relevant experience OR * Bachelor's Level Degree and a minimum of 15 years of experience Base Pay Range: $0.00 - $0.00 Primary Location: USA-CA-Milpitas-KLA KLA's total rewards package for employees may also include participation in performance incentive programs and eligibility for additional benefits including but not limited to: medical, dental, vision, life, and other voluntary benefits, 401(K) including company matching, employee stock purchase program (ESPP), student debt assistance, tuition reimbursement program, development and career growth opportunities and programs, financial planning benefits, wellness benefits including an employee assistance program (EAP), paid time off and paid company holidays, and family care and bonding leave. Interns are eligible for some of the benefits listed. Our pay ranges are determined by role, level, and location. The range displayed reflects the pay for this position in the primary location identified in this posting. Actual pay depends on several factors, including state minimum pay wage rates, location, job-related skills, experience, and relevant education level or training. We are committed to complying with all applicable federal and state minimum wage requirements where applicable. If applicable, your recruiter can share more about the specific pay range for your preferred location during the hiring process. KLA is proud to be an Equal Opportunity Employer. We will ensure that qualified individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us at___ or at +1-408-352-2808 to request accommodation. Be aware of potentially fraudulent job postings or suspicious recruiting activity by persons that are currently posing as KLA employees. KLA never asks for any financial compensation to be considered for an interview, to become an employee, or for equipment. Further, KLA does not work with any recruiters or third parties who charge such fees either directly or on behalf of KLA. Please ensure that you have searched ___ for legitimate job postings. KLA follows a recruiting process that involves multiple interviews in person or on video conferencing with our hiring managers. If you are concerned that a communication, an interview, an offer of employment, or that an employee is not legitimate, please send an email to ___ to confirm the person you are communicating with is an employee. We take your privacy very seriously and confidentially handle your information.

Senior Lead, Principal Data Scientist / Associate Director - Data Science. Work closely with cross‑functional teams, including data scientists, data engineers, product managers, and business experts to ensure smooth development of RGM models and translate outcomes to business stakeholders. Princip

Senior Lead, Principal Data Scientist / Associate Director - Data Science. Work closely with cross‑functional teams, including data scientists, data engineers and product managers and business experts to ensure the smooth development of RGM models and translate outcomes to business stakeholders. P

A leading analytics firm is seeking a Principal Data Scientist for commercial analytics based in New Jersey.The candidate will lead client-facing projects, guide offshore teams, and drive data science solutions.Key qualifications include 8-12 years of experience, expertise in machine learning and st