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 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 supportive environment where your contributions are valued and your career can flourish.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist II
✨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. Share it on platforms like GitHub or your personal website to give potential employers a taste of what you can do.
✨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 experience aligns with the responsibilities listed in the job description.
✨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
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your Python programming skills and experience with OpenAI APIs in your application. We want to see how you can bring your data science expertise to the table, so don’t hold back!
Tailor Your Application:Take a moment to customise your application for the Senior Data Scientist II role. Mention specific projects or experiences that align with our work in GenAI and machine learning. This shows us you’re genuinely interested in what we do!
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 skills shine through without unnecessary fluff.
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 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.
