At a Glance
- Tasks: Design and deploy AI/ML solutions that drive real business impact across various functions.
- 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 opportunities.
- Why this job: Experiment with cutting-edge tech and see your work make a measurable difference globally.
- Qualifications: Strong Python skills and experience with OpenAI APIs and machine learning fundamentals.
The predicted salary is between 60000 - 80000 £ per year.
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
- Strong Python programming skills.
- 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 II 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 thrives on innovation, offering employees the chance to engage in diverse projects that have a tangible impact across the organisation. With ample opportunities for professional growth and a commitment to cutting-edge technology, you will find a rewarding environment where your contributions are valued and recognised.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist II in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with current employees at LexisNexis. A friendly chat can sometimes lead to opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving GenAI and ML solutions. This gives you a chance to demonstrate your expertise and creativity beyond just a CV.
✨Tip Number 3
Prepare for the interview by brushing up on your Python and machine learning fundamentals. Be ready to discuss your past projects and how they’ve made an impact—this is your time to shine!
✨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, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Senior Data Scientist II in London
Some tips for your application 🫡
Show Your Versatility:As a Senior Data Scientist II, we want to see your range! Highlight your experience across GenAI, traditional ML, and data engineering. Make sure to showcase projects where you've tackled diverse problems and delivered impactful solutions.
Be Specific About Your Skills:When listing your skills, be specific about your Python programming, experience with OpenAI APIs, and familiarity with tools like Databricks and AWS. We love details that show how you’ve used these technologies in real-world applications.
Tell Us About Your Impact:We’re all about making a measurable difference. In your application, share examples of how your work has driven business impact. Use metrics or outcomes to illustrate the success of your projects—numbers speak volumes!
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 ensure it gets the attention it deserves. Plus, it makes the process smoother for everyone involved!
How to prepare for a job interview at 慨正橡扯
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, Databricks, and AWS. Brush up on your experience with OpenAI APIs and LLM workflows, as these will likely come up during the interview.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled diverse data science problems. Highlight your end-to-end project ownership and how your solutions made a measurable impact on previous teams or projects.
✨Understand the Business Impact
Familiarise yourself with how data science drives decisions in various business functions like Product, Sales, and Marketing. Be ready to explain how your work can support these areas and contribute to overall business goals.
✨Prepare for Technical Questions
Expect technical questions that test your knowledge of machine learning fundamentals, prompt engineering, and data pipelines. Practise explaining complex concepts in simple terms, as you’ll need to communicate effectively with stakeholders.
