At a Glance
- Tasks: Build and deploy AI and ML solutions that drive real business value.
- Company: Join a fast-moving Data Science & AI team at LexisNexis.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborate across teams to deliver innovative solutions and insights.
- Why this job: Make a real impact with cutting-edge technology in a dynamic environment.
- Qualifications: Strong Python skills and experience with machine learning and cloud platforms.
The predicted salary is between 60000 - 80000 € per year.
Are you ready to grow your data science expertise and work on impactful AI and machine learning projects? Would you enjoy building advanced analytics, machine learning, and GenAI solutions that drive real business value?
About Our Team
We are a fast-moving, high-impact Data Science & AI team building real-world GenAI and ML solutions across the LexisNexis business. Our work powers smarter decisions for Product, Sales, Finance, Marketing, Customer Success, and Engineering—everything from predictive models to enterprise GenAI applications to automation that transforms how teams operate. We are data science generalists who enjoy variety. One day, it may be designing a new GenAI workflow, the next it may be deploying a model into Salesforce or developing a pipeline in Databricks. We work closely with stakeholders to build practical solutions that are used and deliver measurable impact. If you want to experiment, build, ship, and see your work make a difference across a global organisation, you will feel right at home with us.
About The Role
We are seeking a Data Scientist III who is a strong 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 help design, build, and deploy AI and ML solutions that support key business functions across Product, Sales, Finance, Marketing, Customer Success, and Engineering. You will contribute across the full solution lifecycle, including problem framing, data preparation, modelling, experimentation, prompt engineering, deployment, monitoring, and stakeholder communication. This position is ideal for a versatile data scientist who enjoys solving diverse problems, working across multiple systems, and contributing to measurable business impact.
Responsibilities
- Build GenAI applications using OpenAI APIs, embeddings, vector search, and RAG.
- Apply prompt engineering and help define evaluation approaches for GenAI outputs.
- Develop and deploy ML models (e.g., churn, propensity-to-buy, sentiment/feedback, lead scoring, customer intelligence).
- Own the full ML lifecycle: data prep, experimentation, deployment, and monitoring.
- Build and optimize feature pipelines and model scoring jobs with Python, Databricks, Spark, and Delta Lake.
- Use AWS (S3, Redshift, Lambda) for data automation and orchestration.
- Improve pipeline data quality, observability, lineage, and documentation.
- Integrate models/data with enterprise platforms (Salesforce, Oracle Fusion/Service Cloud/PeopleSoft).
- Deliver real-time and batch workflows to improve CRM, sales, service, and marketing operations.
- Partner cross-functionally to define KPIs, generate actionable insights, communicate clearly, and drive adoption via demos/docs/training.
Requirements
- Strong Python programming skills.
- 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 working with behavioral or business datasets.
- Ability to work across machine learning, analytics, data engineering, and integrations.
- Ability to contribute to end-to-end solutions spanning data, models, APIs, and automation workflows.
Data Scientist III in London employer: LexisNexis
At LexisNexis, we pride ourselves on being an exceptional employer that fosters a dynamic and collaborative work environment. Our Data Science & AI team is at the forefront of innovation, offering employees the chance to work on impactful projects that drive real business value across various functions. With a strong emphasis on professional growth, diverse problem-solving, and cutting-edge technology, we empower our team members to experiment and see their contributions make a tangible difference in a global organisation.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist III in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with data science communities. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving GenAI and machine learning. Share it on platforms like GitHub or your personal website to catch the eye of recruiters.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and problem-solving abilities. Practice common data science interview questions and be ready to discuss your past projects and their impact.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Data Scientist III in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Data Scientist III role. Highlight your expertise in GenAI, machine learning, and any relevant projects you've worked on. We want to see how you can contribute to our team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for data science and how it aligns with our mission at StudySmarter. Tell us about specific projects or experiences that demonstrate your ability to drive real business value.
Showcase Your Projects:If you've worked on any cool AI or machine learning projects, make sure to include them in your application. We love seeing practical examples of your work, especially if they relate to the responsibilities outlined in the job description.
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 shows you're keen on joining our awesome team!
How to prepare for a job interview at LexisNexis
✨Know Your Tech Stack
Make sure you’re familiar with the tools and technologies mentioned in the job description, like Python, Databricks, and AWS. Brush up on your skills with OpenAI APIs and machine learning fundamentals, as these will likely come up during technical discussions.
✨Showcase Your Projects
Prepare to discuss specific projects where you've built or deployed AI and ML solutions. Highlight your role in the full solution lifecycle, from data preparation to deployment, and be ready to explain the impact your work had on the business.
✨Understand the Business Context
Research LexisNexis and understand how data science impacts various functions like Product, Sales, and Marketing. Be prepared to discuss how your work can drive real business value and improve decision-making across these areas.
✨Practice Problem Framing
Since the role involves problem framing and stakeholder communication, practice articulating how you would approach a data science problem. Think about how you would define KPIs and generate actionable insights that align with business goals.
