Senior Data Scientist I
RELX is hiring a Senior Data Scientist I. Level rates it ; you can apply on Level.
AI in this role
Senior Data Scientist building end-to-end AI analytics solutions, machine learning models, and generative AI applications for product insights.
Are you passionate about using AI, advanced analytics, and data science to solve complex problems and influence product strategy?
Do you enjoy building end-to-end solutions that transform data into actionable insights and measurable business value?
About our Team
At LexisNexis Intellectual Property Solutions, our mission is to bring clarity to innovation by delivering better outcomes to the innovation community. Each and every day, the work our team does supports the development of new technologies and processes that ultimately advance humanity. Helping our customers reach their goals is our primary focus. We enable innovators to accomplish more by helping them make informed decisions, be more productive, comply with regulations and ultimately achieve superior results. Our overall success is measured by how well we deliver these results. We are proud to directly support and serve these innovators in their endeavors to better humankind.
About the Role
As a Senior Data Scientist in the Global Product Insights team, you will build end-to-end AI analytics solutions that turn complex data into actionable insights and support informed product and business decisions. You will own delivery from problem definition and data preparation through development, deployment, evaluation, and continuous improvement. Working closely with product, analytics, and engineering teams, you will apply data science, AI, and data engineering expertise to deliver scalable solutions that create measurable impact.
Responsibilities
- Translate product and business questions into clearly defined analytics and AI use cases, with measurable success criteria.
- Design, develop, and deploy end-to-end AI analytics solutions, from data ingestion and transformation to models, applications, and stakeholder-facing insights.
- Build and maintain scalable data pipelines using SQL, Python, and Databricks, ensuring data quality, reliability, and reproducibility.
- Apply machine learning and generative AI, including LLMs, and agentic workflows, where appropriate to improve analytics and decision support.
- Analyse product usage and other relevant data to identify patterns, explain performance, and uncover opportunities to improve customer and business outcomes.
- Establish evaluation and monitoring practices covering analytical accuracy, AI output quality, reliability, performance, cost, and business impact.
- Collaborate with engineering and analytics teams to integrate solutions into existing platforms and workflows, following sound software engineering and data engineering practices.
- Communicate findings and recommendations clearly, contribute to technical decisions, and share best practices with colleagues.
Requirements
- Demonstrated experience delivering data science and AI solutions from concept to production, supported by equivalent practical experience.
- Strong SQL expertise, including complex queries, data transformation, and performance optimisation across large datasets.
- Strong Python proficiency for data analysis, machine learning, automation, and production-quality application development.
- Robust knowledge of data engineering, including data modelling, ETL/ELT, pipeline orchestration, testing, and data quality management.
- Hands-on experience with Databricks and Apache Spark to build and operate scalable data pipelines and analytics or AI workflows.
- Proven proficiency in applied AI, demonstrated through delivered solutions using machine learning and modern generative AI techniques, including LLMs, prompting, retrieval, and evaluation.
- Strong statistical and analytical skills, with sound judgement in selecting methods, validating results, and interpreting uncertainty.
- Experience deploying and maintaining solutions using version control, automated testing, CI/CD, and model or application monitoring.
- Strong communication and stakeholder collaboration skills, with the ability to work independently, translate business needs into technical solutions, and explain results to non-technical audiences.
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.
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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How we rate this
Senior Data Scientist I at RELX rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
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Skills and AI tools this role asks for
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where data science was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where generative ai was part of your work. What did you do?
- Tell me about a project where llms was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI agents, Data Science, Machine learning, Generative AI, and LLMs. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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