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# Senior Data Scientist I

- **Company:** LexisNexis
- **Location:** London, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Automation of Tests, Big Data, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Transformation, Database Queries, Decision Support Systems, HP Systems Insight Manager, Python (Programming Language), Machine Learning, Performance Tuning, Software Engineering, SQL Databases, Data Ingestion, Large Language Models, Apache Spark, Data Analytics, Software Version Control, Data Pipelines, Automation Anywhere, Databricks
- **Published:** October 9, 2026
- **Apply:** https://relx.wd3.myworkdayjobs.com/LexisNexisLegal/job/Farringdon/Senior-Data-Scientist-I_R119396

## About the Role

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?, * 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.

## Description

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., * 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.