Senior Data Scientist

Posted 6 Days Ago
7 Locations
In-Office or Remote
95K-191K Annually
Senior level
Information Technology • Legal Tech • Analytics
The Role
Design, build, evaluate, and scale production-ready AI solutions (LLMs, NLP, retrieval, RAG, knowledge graphs) to support scientific discovery. Lead architecture, mentor data scientists, partner with engineering and product, and measure model quality, trustworthiness, and user impact.
Summary Generated by Built In

Senior Data Scientist

AI for Science, Research Intelligence & Knowledge Discovery

Build AI That Helps Advance Human Knowledge

What if your next AI model could help accelerate a medical breakthrough, uncover a critical scientific insight, or help researchers solve some of humanity's greatest challenges?

At Elsevier, data science is about far more than algorithms and model performance. It is about applying advanced AI to help researchers, clinicians, educators, and institutions discover knowledge, assess evidence, generate insights, and advance science for the benefit of society.

Every day, millions of researchers rely on our products to navigate an ever-growing universe of scientific information. As a Senior Data Scientist, you will help build the intelligent systems that make scientific knowledge more discoverable, trustworthy, connected, and actionable.

This is AI with purpose. This is technology in service of scientific progress.

About the Role

As a Senior Data Scientist, you will design, build, evaluate, and scale advanced AI solutions that power scientific discovery, research intelligence, knowledge enrichment, and decision support across the global research ecosystem.

You will work on some of the most challenging problems in applied AI, combining machine learning, natural language processing, large language models, retrieval systems, knowledge graphs, and generative AI to help researchers uncover insights faster and make better decisions.

Success in this role requires deep technical expertise, sound judgment, scientific rigor, and the ability to transform complex problems into trusted, production-ready AI solutions that create measurable impact.

About the team

As part of a growing team of Data Scientists, you will take on some of the hardest problems in science. This team is building intelligent systems that can reason across scientific publications, research data, knowledge graphs, ontologies, metadata, taxonomies, citations, and content spanning every scientific discipline

What You'll Do

  • Design, develop, and deploy advanced machine learning, NLP, retrieval, and generative AI solutions that support scientific discovery and knowledge exploration.
  • Build and optimize LLM-powered applications, including question answering, literature summarization, semantic search, research insight generation, and evidence-grounded AI experiences.
  • Develop retrieval-augmented generation (RAG) systems that connect AI models with trusted scientific and scholarly content.
  • Create intelligent capabilities for search, ranking, recommendation, entity extraction, classification, enrichment, and decision support.
  • Design evaluation frameworks that measure quality, relevance, reliability, grounding, trustworthiness, and user impact.
  • Integrate knowledge graphs, ontologies, taxonomies, citations, metadata, and scientific domain knowledge into AI workflows.
  • Partner with engineering teams to produce, monitor, optimize, and continuously improve AI systems at scale.
  • Lead technical discovery, influence solution architecture, and guide methodological decisions across initiatives.
  • Mentor fellow data scientists and contribute to a culture of technical excellence, experimentation, and responsible AI.
  • Collaborate closely with Product, Engineering, Research, Editorial, UX, and domain experts to solve complex scientific and business challenges.

What We're Looking For

  • Significant hands-on experience in Data Science, Machine Learning, Artificial Intelligence, NLP, Information Retrieval, Statistics, Computer Science, or a related quantitative discipline.
  • Advanced expertise in developing and deploying machine learning, NLP, retrieval, and generative AI solutions in production environments.
  • Experience working with modern LLMs, prompt engineering, model evaluation, retrieval systems, and AI-powered workflows.
  • Extensive Python programming skills and a track record of building maintainable, production-quality software.
  • Experience designing and implementing RAG systems, semantic search, vector retrieval, embeddings, ranking, or recommendation solutions.
  • Deep understanding of machine learning fundamentals, experimentation, model evaluation, statistical analysis, and performance measurement.
  • Experience with modern AI and ML frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain, LangGraph, or equivalent technologies.
  • Experience working with large-scale structured, semi-structured, and unstructured datasets, particularly text-rich or content-heavy data.
  • A passion for advancing science, expanding access to knowledge, and building AI systems that create meaningful real-world impact.

Why Join Elsevier

Because your work will matter.

You will help build AI systems that enable researchers to discover knowledge faster, uncover hidden connections, assess evidence more effectively, and accelerate scientific progress around the world.

You will have the opportunity to:

  • Solve some of the most challenging AI problems in science and knowledge discovery.
  • Work with one of the world's richest collections of scientific, biomedical, and scholarly data.
  • Build next-generation AI systems using LLMs, retrieval, knowledge graphs, semantic search, and generative AI.
  • Create trusted technologies that support researchers, clinicians, educators, institutions, and innovators worldwide.
  • Influence how AI is designed, evaluated, governed, and trusted in high-impact scientific environments.
  • Collaborate with exceptional colleagues across data science, engineering, product, research, editorial, and domain expertise.
  • Mentor others while helping shape the future of AI-powered scientific discovery.
  • Contribute directly to a mission dedicated to advancing science, improving health outcomes, and expanding human knowledge.

At Elsevier, AI is not just about what technology can do. It is about what humanity can achieve when knowledge becomes more accessible, discoverable, and actionable.

That is the impact of your work.

U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New York, the base pay range is $104,800 - $174,700.If performed in New York City, the base pay range is $114,300 - $190,500.If performed in Rochester, NY, the base pay range is $95,300 - $158,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. 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.

USA Job Seekers:

EEO Know Your Rights.

Skills Required

  • Significant hands-on experience in Data Science, Machine Learning, AI, NLP, or Information Retrieval
  • Advanced expertise building and deploying machine learning, NLP, retrieval, and generative AI solutions in production
  • Experience working with modern LLMs, prompt engineering, model evaluation, and retrieval systems
  • Extensive Python programming skills and track record of building maintainable, production-quality software
  • Experience designing and implementing RAG systems, semantic search, vector retrieval, embeddings, ranking, or recommendation solutions
  • Deep understanding of machine learning fundamentals, experimentation, model evaluation, and statistical analysis
  • Experience with AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain, LangGraph, or equivalent
  • Experience working with large-scale structured, semi-structured, and unstructured, text-rich datasets
  • Ability to lead technical discovery, influence solution architecture, and guide methodological decisions
  • Mentoring and collaboration with cross-functional teams (Product, Engineering, Research, UX, domain experts)
  • Passion for advancing science and building responsible, trustworthy AI

RELX Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about RELX and has not been reviewed or approved by RELX.

  • Retirement Support Retirement support is positioned as a meaningful part of total rewards through a 401(k) plan with matching contributions, alongside other financial protections such as life and disability coverage. Tuition reimbursement and share purchase access further broaden the financial value of the package beyond base salary.
  • Leave & Time Off Breadth Leave and time off breadth appears strong, with generous vacation allowances, mental health days, and options like sabbaticals and tiered PTO by tenure. Parental and caregiving leaves are described in detail, reinforcing time-away benefits as a standout component of the overall package.
  • Wellbeing & Lifestyle Benefits Wellbeing and lifestyle benefits are supported by offerings such as mental health support (e.g., app access), EAP resources, gym-related perks, and wellness incentives. Flexible working hours and related work-life supports add to the perceived day-to-day value of benefits.

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The Company
HQ: London
10,001 Employees
Year Founded: 1880

What We Do

RELX is a global provider of information-based analytics for professional and business customers across industries. We help scientists make new discoveries, doctors and nurses improve the lives of patients and lawyers win cases. We prevent online fraud and money laundering, and help insurance companies evaluate and predict risk. Our events enable customers to learn about markets, source products and complete transactions. In short, we enable our customers to make better decisions, get better results and be more productive. We do this by leveraging a deep understanding of our customers to create innovative solutions which combine content and data with analytics and technology in global platforms. RELX serves customers in more than 180 countries and has offices in about 40 countries. It employs approximately 30,000 people of whom almost half are in North America. We operate in four major market segments: Scientific, Technical & Medical; Risk & Business Analytics; Legal; and Exhibitions.

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