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 measurable insights and solutions.
- 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.
About our team
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? 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 organization, 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, and 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 behavioural 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: 慨正橡扯
At LexisNexis, we pride ourselves on being an exceptional employer that fosters a dynamic and collaborative work culture. Our Data Science & AI team is dedicated to innovation, providing employees with the opportunity to work on cutting-edge projects that have a tangible impact across various business functions. With a strong emphasis on professional growth, we offer continuous learning opportunities and the chance to experiment with advanced technologies in a supportive environment, making it an ideal place for data scientists looking to make a meaningful difference.
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 understanding the business impact of your work. Be ready to discuss how your projects have driven real value—this is what employers want to hear!
✨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 🫡
Show Off Your Skills:Make sure to highlight your strong Python programming skills and experience with OpenAI APIs. We want to see how you can apply your knowledge in real-world scenarios, so don’t hold back on showcasing your projects!
Tailor Your Application:Customise your application to reflect the specific requirements of the Data Scientist III role. Mention your experience with machine learning fundamentals and any relevant tools like Databricks or AWS that align with what we’re looking for.
Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate straightforward communication, so make sure your experience and achievements are easy to understand and directly related to the role.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for this exciting opportunity with our Data Science & AI team.
How to prepare for a job interview at 慨正橡扯
✨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 Problem-Solving Skills
Prepare to discuss specific examples of how you've tackled diverse data science problems in the past. Think about projects where you designed, built, and deployed solutions that had a measurable impact. This will demonstrate your versatility and ability to contribute across various business functions.
✨Communicate Clearly
Since this role involves partnering with cross-functional teams, practice explaining complex concepts in simple terms. Be ready to discuss how you’ve communicated insights and driven adoption of your solutions through demos or training sessions.
✨Ask Insightful Questions
Prepare thoughtful questions about the team’s current projects and challenges. This shows your genuine interest in the role and helps you understand how you can make a real difference within the organisation. Plus, it gives you a chance to assess if the company culture aligns with your values.
