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Senior Data Scientist Machine Learning Jobs in Raleigh, NC

... grade machine learning? Do you enjoy building reliable, scalable applications that transform ... a Senior Data Scientist II with deep expertise in Generative AI, Retrieval-Augmented Generation ...

... grade machine learning? Do you enjoy building reliable, scalable applications that transform ... a Senior Data Scientist II with deep expertise in Generative AI, Retrieval-Augmented Generation ...

Data Scientist

Cary, NC · On-site

$65 - $70/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Experience in developing Machine Learning models using Python (preferably in the cloud ... Visualize data, create reports, and present findings to senior management and cross-functional ...

Required : • Machine Learning techniques • Unsupervised - K-means Clustering, PCA - Dimension ... • Data Science Languages - SAS, SAS Enterprise Miner, R Programming, Python, Spark • ...

AVP, AI (Data Science/Engineer) Remote - EST

Raleigh, NC · Remote

$185K - $235K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Reporting to the SVP of AI & Automation, you will lead the development of multi-agent AI solutions ... This role is focused on applying AI, machine learning, and data science to solve high-value ...

AVP, AI (Data Science/Engineer) Remote - EST

Raleigh, NC · Remote

$185K - $235K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Reporting to the SVP of AI & Automation, you will lead the development of multi-agent AI solutions ... This role is focused on applying AI, machine learning, and data science to solve high-value ...

Senior Data Scientist

Cary, NC · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

What You'll Do Epic Games is looking for a Senior Data Scientist to support the meta-progression systems area. You'll apply mixed methods to own the end-to-end life cycle of creating data assets ...

Senior Data Scientist

Cary, NC · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

What You'll Do Epic Games is looking for a Senior Data Scientist to support the meta-progression systems area. You'll apply mixed methods to own the end-to-end life cycle of creating data assets ...

Data Scientist

Raleigh, NC · On-site

$110 - $170/hr

* Design and implement statistical and machine learning models for time-series forecasting, anomaly ... Data Science, or a related quantitative field. * 3+ years of experience (with Bachelor's), 2+ years ...

Embedded Data Scientist

Morrisville, NC · On-site

$130K - $150K/yr

Embedded Data Scientist Full-time Morrisville, NC, US Exclusive confidential search -- details ... At least 2 years of experience with machine-learning frameworks such as TensorFlow and Keras * At ...

Showing results 41-60

Senior Data Scientist Machine Learning information

See Raleigh, NC salary details

$40.3K

$138.5K

$195.4K

How much do senior data scientist machine learning jobs pay per year?

As of Aug 17, 2026, the average yearly pay for senior data scientist machine learning in Raleigh, NC is $138,483.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,200.00 and $161,900.00 per year, depending on experience, location, and employer.

What does a senior data scientist specializing in machine learning do?

A Senior Data Scientist in Machine Learning leads the development, implementation, and optimization of advanced statistical and machine learning models to solve business problems. They analyze large, complex datasets, design predictive algorithms, and collaborate with cross-functional teams to integrate models into production systems. Additionally, they mentor junior data scientists, contribute to setting technical strategy, and often communicate findings to stakeholders to drive data-driven decision-making.

What are the key skills and qualifications needed to thrive as a senior data scientist in machine learning?

To thrive as a Senior Data Scientist in Machine Learning, you need advanced expertise in statistics, programming (Python or R), and machine learning algorithms, typically backed by a relevant degree (such as in computer science or mathematics) and several years of experience. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and cloud platforms (AWS, GCP, or Azure), as well as experience with big data technologies, is essential. Strong problem-solving, communication, and project leadership skills help drive impactful solutions and foster collaboration across teams. These skills ensure the successful design, deployment, and scaling of machine learning models that deliver business value.

How does a senior data scientist specializing in machine learning typically collaborate with cross-functional teams?

Senior Data Scientists in Machine Learning often work closely with product managers, software engineers, and business analysts to understand project goals and translate them into actionable data solutions. They are responsible for communicating complex technical concepts to non-technical stakeholders, ensuring that ML models align with business objectives. Collaboration frequently involves participating in regular strategy meetings, reviewing data pipelines with engineering teams, and providing insights that guide product development. This cross-disciplinary teamwork is essential for successfully deploying machine learning models into production environments.

What is the difference between Senior Data Scientist Machine Learning vs Data Scientist?

AspectSenior Data Scientist Machine LearningData Scientist
Required CredentialsMaster's or PhD in CS, Statistics, or related field; experience with ML frameworksBachelor's or Master's in relevant field; foundational knowledge of data analysis
Work EnvironmentAdvanced analytics teams, R&D, product developmentData analysis teams, business intelligence, reporting
Employer & Industry UsageTech companies, finance, healthcare, e-commerceSimilar industries, often entry to mid-level roles

The main difference is that Senior Data Scientist Machine Learning roles require more experience, advanced skills in ML frameworks, and often involve leading projects. Data Scientists typically focus on data analysis and reporting with less emphasis on complex ML models. Senior roles also tend to involve mentorship and strategic input.

What are the most commonly searched types of Data Scientist Machine Learning jobs in Raleigh, NC?

The most popular types of Data Scientist Machine Learning jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Senior Data Scientist Machine Learning jobs?

Cities near Raleigh, NC with the most Senior Data Scientist Machine Learning job openings:

Sr Data Scientist II

LexisNexis

Raleigh, NC • On-site

Full-time

Posted 8 days ago


LexisNexis rating

7.6

Company rating: 7.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

189th of 492 rated business services


Job description

Are you excited about shaping the next generation of AI-powered legal technology through generative AI, retrieval systems, and production-grade machine learning?
Do you enjoy building reliable, scalable applications that transform complex AI capabilities into impactful customer solutions?
About our Team
LexisNexis Legal & Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of RELX (http://www.relx.com), a global provider of information-based analytics and decision tools for professional and business customers. Our company has been a long-time leader in deploying AI and advanced technologies to the legal market to improve productivity and transform the overall business and practice of law, deploying ethical and powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model from today's top model creators for each individual legal use case. The company employs over 2,000 technologists, data scientists, and experts to develop, test, and validate solutions in line with RELX Responsible AI Principles (https://stories.relx.com/responsible-ai-principles/index.html).
About the Role
We are looking for a Senior Data Scientist II with deep expertise in Generative AI, Retrieval-Augmented Generation (RAG), and agentic AI systems, combined with strong software-engineering fundamentals and demonstrated ownership of production applications. This role will focus on improving LLM-powered drafting and retrieval solutions through advanced search, embeddings, reranking, evaluation, and production-grade ML components.
The successful candidate must be able to independently design, refactor, test, review, deploy, and support clean, reliable Python applications. This includes separating agent responsibilities, designing for failure, applying sound algorithmic reasoning, and establishing appropriate logging, monitoring, testing, and operational controls.
The ideal candidate has advanced Python proficiency, experience with OpenSearch or Solr, success working in monorepo environments, and a strong record of cross-functional delivery.
Key Responsibilities
  • Architect modular agentic applications with clear separation among retrieval, prompt construction, model invocation, tool execution, state and history management, orchestration, validation, and response formatting.
  • Independently refactor complex or legacy Python code to improve correctness, readability, modularity, extensibility, testability, and runtime performance.
  • Own production readiness for AI components, including input validation, exception handling, timeout management, retries with backoff, fallback behavior, configuration management, and secure handling of credentials.
  • Establish observability for LLM and retrieval workflows through structured logging, metrics, distributed tracing, alerting, and actionable error reporting.
  • Design clear interfaces and data contracts between retrieval, orchestration, model, and downstream application components.
  • Write comprehensive unit, integration, regression, and end-to-end tests, including tests for failure modes, malformed model responses, empty retrieval results, and unavailable dependencies.
  • Review Python and agentic application code, identify architectural and operational risks, and provide actionable feedback aligned with production engineering standards.
  • Diagnose and optimize latency, memory usage, retrieval performance, token consumption, model cost, and application scalability.
  • Apply appropriate data structures, algorithms, and computational-complexity analysis when designing and optimizing solutions.
  • Participate in production deployments, incident investigation, root-cause analysis, remediation, and continuous reliability improvements.

Required Qualifications
  • Advanced Python proficiency demonstrated through independently designing, implementing, debugging, testing, reviewing, and refactoring production applications.
  • Strong command of Python fundamentals, standard data structures, common algorithms, object-oriented and functional design principles, type annotations, and time and space complexity analysis.
  • Demonstrated ability to transform prototype or experimental code into modular, maintainable, observable, and production-ready systems.
  • Strong understanding of software design principles, including separation of concerns, dependency injection, interface design, configuration management, and effective abstraction.
  • Experience implementing automated unit, integration, regression, and end-to-end testing using tools such as pytest, including appropriate mocking of external services.
  • Experience designing resilient distributed applications that account for timeouts, retries, rate limits, partial failures, malformed responses, idempotency, and graceful degradation.
  • Experience with production observability, including structured logging, metrics, tracing, alerting, and incident troubleshooting.
  • Demonstrated ability to conduct rigorous code reviews and identify correctness, maintainability, performance, security, testing, and operational risks.
  • Experience taking technical ownership of applications across their lifecycle, from design and experimentation through deployment, monitoring, incident response, and ongoing improvement.
  • Strong understanding of production LLM concerns, including structured output validation, context management, model and tool failures, prompt versioning, token and cost controls, security, and evaluation.

Preferred Qualifications
  • Experience with Python quality tooling such as pytest, ruff, mypy, profiling tools, and automated CI quality gates.
  • Experience defining typed schemas and validating LLM inputs and outputs using tools such as Pydantic.
  • Experience building evaluation frameworks for agentic systems, including task-completion, retrieval-quality, groundedness, hallucination, latency, reliability, and cost metrics.
  • Experience implementing model fallbacks, tool-use controls, guardrails, human-in-the-loop workflows, and auditability for AI applications.
  • Experience supporting production services and participating in incident response, root-cause analysis, and post-incident remediation.

The successful candidate will:
  • Demonstrate senior-level Python proficiency and sound computer-science fundamentals.
  • Treat correctness, maintainability, testing, resilience, security, and observability as core design requirements.
  • Recognize architectural issues and improve code beyond simply making it functional.
  • Independently review and refactor complex agentic application code.
  • Make clear engineering tradeoffs involving quality, latency, scalability, reliability, and cost.
  • Take end-to-end ownership from experimentation through production deployment and operational support.
  • Communicate technical decisions and code-review feedback clearly and constructively.
  • Combine strong LLM and retrieval expertise with disciplined software-engineering practices.

Work in a Way That Works for You
We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.
Working Pattern
Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.
About the Business
LexisNexis Legal & Professional® provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis® and Nexis® services. #AIFluent
U.S. National Base Pay Range: $104,900 - $174,700. Geographic differentials may apply in some locations to better reflect local market rates.If performed in Illinois, the base pay range is $110,100 - $183,500.If performed in Chicago, IL, the base pay range is $115,400 - $192,200.This job is eligible for an annual incentive bonus.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.
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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
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