At a Glance
- Tasks: Lead impactful data science projects using advanced machine learning and analytics solutions.
- Company: Join LexisNexis Legal, a leader in legal and tax information solutions.
- Benefits: Enjoy flexible working hours, generous holiday allowance, and extensive learning resources.
- Why this job: Make a real impact with cutting-edge technology in a dynamic team environment.
- Qualifications: Experience in data science, machine learning, and cloud platforms is essential.
- Other info: Collaborate across teams and drive measurable business outcomes.
The predicted salary is between 36000 - 60000 ÂŁ per year.
Join to apply for the Senior Data Scientist II role at LexisNexis Legal. 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.
Key responsibilities:
- AI, GenAI and Machine Learning: Build GenAI applications using OpenAI APIs, embeddings, vector search, and retrieval augmented generation. Develop advanced prompt engineering patterns and automated evaluation frameworks. Build and deploy traditional ML models, including churn prediction, propensity to buy, customer sentiment and feedback analysis, lead scoring and customer intelligence models, etc. Own the full model lifecycle, including data preparation, experimentation, deployment, and monitoring.
- Data Engineering and Cloud Work: Build and optimize feature pipelines and model scoring jobs using AWS, Python, Databricks, Spark, and Delta Lake. Leverage AWS services, including S3, Redshift, and Lambda for data automation and orchestration. Ensure data quality, observability, lineage, and documentation across pipelines.
- Enterprise System Integrations: Build and deploy model and data integrations with Salesforce (SFDC), Oracle Fusion, Oracle Service Cloud, Oracle Peoplesoft. Support real time and batch workflows that enhance CRM, sales, customer service, and marketing operations.
- Analytics and Insights: Collaborate with cross functional teams to define KPIs and develop analytics solutions. Provide insights that connect customer behaviour, product usage, finance, and CRM data. Translate insights into actionable recommendations that support product, sales, and customer strategy.
- Productionization, Reliability and Support: Provide L2 and L3 support for AI and ML pipelines. Implement monitoring for model drift, data quality, and prompt performance. Lead root cause analysis and build preventive systems for long‑term stability and reliability.
- Cross‑Functional Collaboration: Partner closely with Product, Engineering, Finance, Sales, Operations, Marketing, and Customer Facing teams. Translate business challenges into AI and ML solutions with clear ROI. Communicate technical concepts in a clear and actionable manner for non‑technical stakeholders. Support the adoption of AI and ML solutions through demos, documentation, and training.
Requirements:
- Core Technical Skills: Direct experience with OpenAI APIs, LLM workflows, and prompt. 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 behavioural datasets.
- Generalist Strengths: 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. Strong communication and stakeholder management skills. Ability to operate independently with minimal direction and actively mentor junior data scientists through technical guidance and best practices. Ability to manage multiple workstreams and deliver independently.
- Nice to Have: Experience with MLflow or other MLOps platforms. Experience with CI or CD and DevOps practices. Experience building customer‑facing or enterprise GenAI applications. Knowledge of engineering analytics or operational metrics.
Why Join Us? If you are fascinated by the changes happening in the legal market and want to get to the heart of innovation in this space, then this is the role for you. Come join our award‑winning, growing team!
Work in a way that works for you: We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long‑term goals. Working flexible hours – flexing the times when you work in the day to help you fit everything in and work when you are the most productive.
Working for you: Generous holiday allowance with the option to buy additional days. Health screening, eye care vouchers, and private medical benefits. Life assurance. Access to a competitive contributory pension scheme. Save As You Earn share option scheme. Travel Season ticket loan. Electric Vehicle Scheme. Maternity, paternity, and shared parental leave. Employee Assistance Programme. Access to emergency care for both the elderly and children. RECARES days, giving you time to support the charities and causes that matter to you. Access to employee resource groups with dedicated time to volunteer. Access to extensive learning and development resources. Access to the employee discounts scheme via Perks at Work.
About our business: LexisNexis, a division of FTSE 100 RELX Group, is a leading provider of legal and tax information, data, analytics, and software solutions to legal service providers around the world. In the UK, our customers include many law firms, the bar and bench, local and central public sector, tax advisors, and many corporate counsels. LexisNexis Enterprise Solution is the division of LexisNexis UK that delivers software solutions, including Lexis Omni, a platform that allows legal professionals to work anywhere, anytime, and however they need.
Senior Data Scientist II in England employer: LexisNexis Legal
Contact Detail:
LexisNexis Legal Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist II in England
✨Tip Number 1
Network like a pro! Reach out to current employees at LexisNexis Legal on LinkedIn. Ask them about their experiences and any tips they might have for the interview process. This can give you insider knowledge and make you stand out.
✨Tip Number 2
Prepare for technical interviews by brushing up on your machine learning fundamentals and coding skills. Practice explaining your past projects clearly, focusing on the impact they had. We want to see how you think and solve problems!
✨Tip Number 3
Showcase your versatility! Be ready to discuss how you've worked across different areas like data engineering, analytics, and AI solutions. Highlight specific examples where you’ve made a measurable difference in previous roles.
✨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 at LexisNexis Legal.
We think you need these skills to ace Senior Data Scientist II in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Data Scientist II role. Highlight your experience with AI, machine learning, and data engineering, as well as any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how you can contribute to our team. Be sure to mention specific projects or technologies that excite you about this role at LexisNexis Legal.
Showcase Your Projects: If you've worked on any interesting data science projects, make sure to include them in your application. Whether it's a GenAI app or a machine learning model, we love seeing real-world applications of your skills. It helps us understand your hands-on experience!
Apply Through Our Website: We encourage you to apply directly through our website. This ensures your application gets to the right people quickly. Plus, it’s super easy to do! Just follow the prompts and let us know why you’d be a great fit for our team.
How to prepare for a job interview at LexisNexis Legal
✨Know Your Data Science Fundamentals
Brush up on your machine learning fundamentals, especially supervised learning and NLP. Be ready to discuss how you've applied these concepts in real-world scenarios, as the role requires a solid understanding of data science principles.
✨Showcase Your Project Experience
Prepare to talk about specific projects where you've built and deployed AI or ML solutions. Highlight your end-to-end ownership of these projects, from ideation to deployment, and be ready to discuss the measurable impact they had on the business.
✨Familiarise Yourself with Tools and Technologies
Make sure you're comfortable discussing tools like Databricks, AWS, and OpenAI APIs. If you have experience with feature pipelines or model scoring jobs, be prepared to share insights on how you optimised these processes.
✨Communicate Clearly with Stakeholders
Practice explaining complex technical concepts in simple terms. The ability to translate business challenges into actionable AI and ML solutions is crucial, so think of examples where you've successfully communicated with non-technical stakeholders.