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For Companies At a Glance
- Tasks: Lead impactful data science projects and build advanced AI solutions.
- Company: Join a fast-moving team at LexisNexis, driving real-world GenAI and ML innovations.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic environment with diverse challenges and excellent career advancement potential.
- Why this job: Make a measurable impact across global teams with cutting-edge technology.
- Qualifications: Strong Python skills and experience with OpenAI APIs and machine learning.
The predicted salary is between 60000 - 80000 £ per year.
hackajob is collaborating with LexisNexis to connect them with exceptional professionals for this role. 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
- 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: hackajob
Contact Detail:
hackajob Recruiting Team
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 your connections in the data science field and let them know you're on the lookout for opportunities. You never know who might have a lead or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving GenAI and machine learning. This will give potential employers a taste of what you can do and how you can make an impact.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with Python, AWS, and any relevant tools like Databricks. Practice makes perfect!
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it gives you a better chance to stand out in the application process.
We think you need these skills to ace Senior Data Scientist II in London
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 your expertise aligns with the role, so don’t hold back on showcasing your best projects!
Tailor Your Application: Take a moment to customise your application for this specific role. Mention your experience with machine learning, data engineering, and analytics, and how you’ve used these skills to drive measurable business impact in previous positions.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points where possible to make it easy for us to read through your qualifications and experiences. We appreciate straightforward communication!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at hackajob
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, OpenAI APIs, 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 project ownership, from ideation to deployment, and how your solutions made a measurable impact.
✨Understand the Business Context
Familiarise yourself with how data science drives decisions in various business functions like Product, Sales, and Marketing. Be ready to discuss how your work can support these areas and contribute to the overall success of the organisation.
✨Ask Insightful Questions
Prepare thoughtful questions about the team’s current projects, challenges they face, and their vision for the future. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.