At a Glance
- Tasks: Lead impactful data science projects and build advanced machine learning models.
- Company: Join a fast-moving, high-impact Data Science & AI team at LexisNexis.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic role with diverse challenges and excellent career advancement potential.
- Why this job: Make a real impact with cutting-edge GenAI solutions across a global organisation.
- Qualifications: Experience in data science, machine learning, and cloud platforms required.
The predicted salary is between 60000 - 80000 € per year.
Are you ready to take your data science expertise to the next level and lead impactful projects? Would you enjoy working on advanced machine learning models and cutting-edge analytics solutions?
About our team: We are a fast-moving, high-impact Data Science & AI team building real-world GenAI and ML solutions across the entire LexisNexis business. Our work powers smarter decisions for Product, Sales, Finance, Marketing, Customer Success, and Engineering—everything from predictive models to enterprise GenAI apps to automation that transforms how teams operate. We are data science generalists who love variety. One day, it is designing a new GenAI workflow, the next it is deploying a model into Salesforce or engineering a pipeline in Databricks. We own our projects end-to-end and partner directly with stakeholders to deliver solutions that get used and make a measurable difference. If you want to experiment, build, ship, and see your work drive real impact across a global organisation, you will feel right at home with us.
About the role: We are seeking a Senior Data Scientist II who is a Data Science Generalist. The ideal candidate is comfortable working across GenAI, traditional machine learning, analytics, data engineering, cloud platforms, and enterprise system integrations. In this role, you will design, build, and deploy AI and ML solutions that support key business functions across Product, Sales, Finance, Marketing, Customer Success, and Engineering. You will work end-to-end across ideation, modelling, experimentation, prompt engineering, deployment, monitoring, and stakeholder communication. This position is ideal for a versatile data scientist who enjoys solving diverse problems, working with multiple systems, and driving measurable business impact.
Responsibilities:
- Build GenAI applications using OpenAI APIs, embeddings, vector search, and retrieval-augmented generation (RAG).
- Design advanced prompt engineering patterns and automated evaluation frameworks for LLM quality and safety.
- Develop and deploy traditional ML models (e.g., churn, propensity, sentiment/feedback, lead scoring, customer intelligence).
- Own the end-to-end model lifecycle: data prep, experimentation, deployment, and monitoring.
- Build and optimize feature pipelines and scoring jobs using Python, Databricks, Spark, Delta Lake, and AWS.
- Use AWS services (S3, Redshift, Lambda) for data automation, orchestration, and scalable processing.
- Ensure data quality, observability, lineage, and documentation across data and ML pipelines.
- Deliver enterprise integrations with Salesforce (SFDC) and Oracle platforms (Fusion, Service Cloud, Peoplesoft) for batch and real-time workflows.
- Create analytics solutions with cross-functional partners: define KPIs, connect customer/product/finance/CRM data, and drive actionable recommendations.
- Productionise reliably: provide L2/L3 support, monitor drift/data quality/prompt performance, run root-cause analysis, and implement preventative fixes.
Requirements:
- Direct experience with OpenAI APIs, LLM workflows, and prompt engineering.
- Solid machine learning fundamentals, including supervised learning, NLP, and feature engineering.
- Experience with Databricks, Spark, and Delta Lake.
- Strong SQL skills with experience working on large datasets.
- Experience with AWS, including S3 and Lambda.
- Familiarity with Redshift, Snowflake, or other cloud data warehouses.
- Experience with behavioral datasets.
- Ability to work across machine learning, data engineering, analytics, and integrations.
- Ability to design end-to-end solutions spanning data, models, APIs, and automation workflows.
Senior Data Scientist in London employer: LexisNexis Legal
At LexisNexis, we pride ourselves on being an exceptional employer that fosters a dynamic and innovative work culture. Our Senior Data Scientists enjoy the opportunity to lead impactful projects while collaborating with cross-functional teams, driving real-world solutions that enhance decision-making across the organisation. With a strong emphasis on employee growth, we provide access to cutting-edge technologies and continuous learning opportunities, ensuring that our team members thrive in their careers while making a meaningful difference in the world of data science.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field and let them know you're on the lookout for opportunities. Attend meetups, webinars, or conferences related to AI and machine learning to meet potential employers and learn about job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving GenAI and machine learning. Use platforms like GitHub to share your code and demonstrate your problem-solving abilities. This will give you an edge when chatting with recruiters.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with OpenAI APIs, Databricks, and AWS. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with stakeholders.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight your versatility and how you can contribute to our data science projects. Let's make an impact together!
We think you need these skills to ace Senior Data Scientist in London
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your data science expertise in your application. We want to see your experience with machine learning models, analytics solutions, and any cool projects you've worked on that demonstrate your versatility.
Tailor Your Application:Don’t just send a generic application! Tailor your CV and cover letter to reflect the specific skills and experiences mentioned in our job description. This shows us you’re genuinely interested in the role and understand what we’re looking for.
Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate well-structured applications that make it easy for us to see your qualifications and how you can contribute to our team.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at LexisNexis Legal
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like OpenAI APIs, Databricks, and AWS. Brush up on your machine learning fundamentals and be ready to discuss specific projects where you've applied these skills.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled diverse data science challenges in the past. Highlight your experience with end-to-end model lifecycles and how your solutions made a measurable impact on business outcomes.
✨Communicate Like a Pro
Since this role involves stakeholder communication, practice explaining complex concepts in simple terms. Be ready to discuss how you’ve collaborated with cross-functional teams and how you ensure everyone is on the same page.
✨Ask Insightful Questions
Prepare thoughtful questions about the team’s current projects and future goals. This shows your genuine interest in the role and helps you understand how you can contribute to their success right from the start.
