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: Enjoy competitive benefits tailored to your location and career growth.
- Other info: Collaborative environment with opportunities for diverse problem-solving.
- Why this job: Make a real impact with cutting-edge GenAI and machine learning projects.
- Qualifications: Strong Python skills and experience with OpenAI APIs and machine learning.
The predicted salary is between 60000 - 80000 £ per year.
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?
About our team: 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 organisation, 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 optimise 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/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.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.
We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
Data Scientist III employer: LexisNexis Risk Solutions
Contact Detail:
LexisNexis Risk Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist III
✨Tip Number 1
Network like a pro! Reach out to current employees at LexisNexis or similar companies on LinkedIn. A friendly chat can give you insider info and might even lead to a referral, which is always a bonus!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those involving GenAI and machine learning. This will help you stand out during interviews and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for the technical interview! Brush up on your Python, SQL, and machine learning fundamentals. Practising coding challenges and case studies related to data science will help you feel more confident when it’s 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 awesome team!
We think you need these skills to ace Data Scientist III
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with GenAI, machine learning, and the specific tools mentioned in the job description. We want to see how your skills align with what we're looking for!
Showcase Your Projects: Include examples of past projects where you've built or deployed AI and ML solutions. We love seeing real-world applications of your work, so don't hold back on the details!
Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, so make sure your key achievements and skills stand out without unnecessary fluff.
Apply Through Our Website: For the best chance of getting noticed, apply directly through our website. It helps us keep track of your application and ensures you’re considered for the role you’re excited about!
How to prepare for a job interview at LexisNexis Risk Solutions
✨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 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. Highlight your experience with the full ML lifecycle, from data preparation to deployment, and be ready to explain your thought process clearly.
✨Understand the Business Impact
Familiarise yourself with how data science can drive business value across different functions like Sales and Marketing. Be prepared to discuss how your work has previously led to measurable outcomes and how you can contribute to the company's goals.
✨Engage with Stakeholders
Since this role involves cross-functional collaboration, think about how you’ve effectively communicated with stakeholders in the past. Prepare to share examples of how you’ve defined KPIs or generated actionable insights that have influenced decision-making.