Time since we first saw it
Day 10
Similar jobs usually come down between day 4 and day 77.
At Relx, jobs usually come down by about day 24.
From 51 similar postings that came down, and 33 of Relx’s. Coming down is not always a hire.
Senior Data Scientist I
Reads like an AI Engineer role: building products on existing AI models.
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingLead design and development of ML and AI-powered systems for complex problems
Own end-to-end solutions from problem framing to production deployment
Design systems that combine retrieval, ranking, and generation
Define and drive evaluation strategies for reliable AI outputs
Mentor other data scientists and guide the team's technical bar
From the employer’s posting
Lead the design and development of machine learning and AI-powered systems for complex, real-world problems
Own end-to-end solutions—from problem framing and experimentation to production deployment and iteration
Design systems that combine retrieval, ranking, and generation to enable intelligent workflows
Define and drive evaluation strategies, ensuring high-quality, reliable, and trustworthy outputs
Mentor and guide other data scientists, helping raise the overall technical bar of the team
What you’ll bring
All qualificationsCore experience
- Significant experience in data science, machine learning, or related field
- Strong Python skills and production-quality, maintainable systems
- Hands-on experience with large language models in applied or production settings
- Experience with retrieval approaches such as embeddings, semantic search, ranking
- Experience with large, complex, unstructured datasets, especially text
Qualification wording
Significant experience in data science, machine learning, or a related field
Strong Python skills with a track record of building production-quality, maintainable systems
Hands-on experience working with large language models (LLMs) in applied or production settings
Experience with retrieval-based approaches (e.g., embeddings, semantic search, ranking)
Experience working with large, complex, and unstructured datasets (especially text)
Posting record
Report an errorActively hiringFirst seen by us 10 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 3, 202610 days ago
- Recorded sightings
- 10
- Last seen by us
- Nov 13, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Relx is hiring
42 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down at a usual pace
- 10% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- Elasticsearch
- MLflow
- SageMaker
- Hugging Face
- PyTorch
- scikit-learn
- TensorFlow
Where the posting names them
- Significant experience in data science, machine learning, or a related field - Strong Python skills with a track record of building production-quality, maintainable systems - Deep understanding of machine learning fundamentals and experience applying them in real-world settings
- Ability to contribute to scalable system design and collaborate effectively with engineering teams - Experience with vector databases or search infrastructure such as Elasticsearch, OpenSearch, Qdrant or similar. Collaboration & Leadership
- Experience designing evaluation frameworks for AI-generated or retrieval-based outputs - Exposure to MLOps tools and practices (e.g., MLflow, Kubeflow, SageMaker) - Experience optimizing systems for performance, scalability, or cost
- Experience working with large, complex, and unstructured datasets (especially text) - Familiarity with ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn, HuggingFace) - Experience with cloud platforms and modern development workflows (Git, CI/CD)
Your next step
Complete your application on relx.wd3.myworkdayjobs.com. The employer’s form will show what is required.
Applying through Workday
- You create an account with each employer before you can upload anything. Every Workday employer has its own account, so one sign-up doesn’t carry over.
- “Autofill with Resume” comes right after sign-in, before the My Information and My Experience steps. Check every field it fills in those steps, since that’s what recruiters see.
- Your application status lives in that employer’s Candidate Home, under the same sign-in.
Already applied? Track this application
Has Relx posted this job before?
Yes. We’ve followed 6 other Senior Data Scientist I jobs there since June 2026. One came down after 0 days. 5 are still up.
Large employers often post one title for several teams, so these can be separate openings.
About Relx
- People
- About 13,644 in 2024.Benefit plan filings (Form 5500)
- Company
- Listed as REL.L.
Demand for AI Engineer roles
New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Job description
Interested in building and shaping AI systems that combine machine learning, retrieval, and modern language models to solve real-world problems
About the team: You’ll work closely with engineering, product, and cross-functional partners to deliver robust, scalable solutions, while helping raise the technical bar across the team.
About the role: We’re looking for a Senior Data Scientist I to lead the design and development of intelligent, data-driven systems that help users explore, understand, and act on complex information.
In this role, you’ll take ownership of high-impact problem areas—driving solutions from concept to production while navigating ambiguity and making key technical decisions. You’ll combine strong machine learning foundations with modern AI approaches to build systems that integrate prediction, retrieval, and generation at scale.
What You’ll Do
- Lead the design and development of machine learning and AI-powered systems for complex, real-world problems
- Own end-to-end solutions—from problem framing and experimentation to production deployment and iteration
- Drive technical direction for key problem areas, making informed trade-offs between modeling approaches, system design, and scalability
- Apply a range of techniques—from classical ML to large language model (LLM) approaches—based on the problem context
- Design systems that combine retrieval, ranking, and generation to enable intelligent workflows
- Define and drive evaluation strategies, ensuring high-quality, reliable, and trustworthy outputs
- Contribute to system architecture and scalability, working closely with engineering teams
- Mentor and guide other data scientists, helping raise the overall technical bar of the team
- Influence product direction by translating technical insights into actionable recommendations
- Collaborate with product teams to design experiments, measure impact, and iterate based on evidence
What We’re Looking For
Core Qualifications
- Significant experience in data science, machine learning, or a related field
- Strong Python skills with a track record of building production-quality, maintainable systems
- Deep understanding of machine learning fundamentals and experience applying them in real-world settings
- Proven experience owning and delivering end-to-end data science or AI projects
- Strong problem-solving skills and ability to navigate ambiguity
- Ability to write clean, tested, well-documented code suitable for collaborative development
- Experience working with cross-functional teams to deliver user-facing data or AI products
AI & Modern Techniques
- Hands-on experience working with large language models (LLMs) in applied or production settings
- Experience with retrieval-based approaches (e.g., embeddings, semantic search, ranking)
- Experience building or contributing to LLM-powered systems involving multi-step reasoning, tool use, or workflow orchestration (e.g., agent-based approaches or frameworks such as LangChain, LangGraph, or similar)
- Strong understanding of when to apply classical machine learning vs. LLM-based approaches
Data & Engineering
- Experience working with large, complex, and unstructured datasets (especially text)
- Familiarity with ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn, HuggingFace)
- Experience with cloud platforms and modern development workflows (Git, CI/CD)
- Ability to contribute to scalable system design and collaborate effectively with engineering teams
- Experience with vector databases or search infrastructure such as Elasticsearch, OpenSearch, Qdrant or similar.
Collaboration & Leadership
- Excellent communication skills with the ability to influence both technical and non-technical stakeholders
- Ability to explain model behavior, trade-offs, and limitations clearly to non-technical audiences
- Experience mentoring or supporting other team members
- Ability to drive projects forward independently while aligning with broader team goals
Nice to Have
- Experience with search, information retrieval, or knowledge systems at scale
- Experience designing evaluation frameworks for AI-generated or retrieval-based outputs
- Exposure to MLOps tools and practices (e.g., MLflow, Kubeflow, SageMaker)
- Experience optimizing systems for performance, scalability, or cost
- Familiarity with frameworks or tools for orchestrating LLM-based workflows and agent-like systems
- Experience working in structured and reproducible development environments (e.g., clear specification of tasks, experiment tracking, and collaborative workflows)
- Interest in emerging paradigms such as spec-driven or AI-assisted development
- Experience with citation-aware, source-grounded, or evidence-based AI systems
Why Join Us
- Lead work on impactful problems involving complex, real-world data
- Build and shape systems that combine machine learning fundamentals with modern AI approaches
- Collaborate with a team focused on quality, scalability, and meaningful outcomes
- Opportunity to influence both technical direction and product evolution
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Please read our Candidate Privacy Policy. 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: