Senior Data Scientist II

Senior Data Scientist II

Full-Time 60000 - 80000 £ / year (est.) No home office possible
LexisNexis Risk Solutions

At a Glance

  • Tasks: Lead impactful data science projects using advanced machine learning and analytics solutions.
  • Company: Join a fast-moving Data Science & AI team at LexisNexis.
  • Benefits: Enjoy competitive benefits tailored to your location and a supportive work environment.
  • Other info: Dynamic role with opportunities for growth and diverse problem-solving.
  • Why this job: Make a real impact with your data science skills across a global organisation.
  • Qualifications: Strong Python skills and experience with OpenAI APIs and machine learning fundamentals.

The predicted salary is between 60000 - 80000 £ per year.

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.

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.

Senior Data Scientist II employer: LexisNexis Risk Solutions

At LexisNexis, we pride ourselves on being an exceptional employer, offering a dynamic work environment in Farringdon where innovation thrives. Our Data Science & AI team fosters a collaborative culture that encourages experimentation and growth, providing employees with opportunities to lead impactful projects and develop cutting-edge solutions. With a focus on employee well-being and a commitment to diversity, we ensure that every team member can contribute meaningfully while enjoying a comprehensive benefits package tailored to their needs.
LexisNexis Risk Solutions

Contact Detail:

LexisNexis Risk Solutions Recruiting Team

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 current employees on LinkedIn or at industry events. Ask them about their experiences and the company culture. This can give you insider info and might even lead to a referral!

✨Tip Number 2

Prepare for the interview by brushing up on your technical skills. Be ready to discuss your experience with Python, machine learning, and any relevant projects. We want to see how you think and solve problems, so practice explaining your thought process.

✨Tip Number 3

Showcase your passion for data science! Bring examples of your work, whether it's a project, a blog post, or a GitHub repo. We love seeing candidates who are genuinely excited about what they do and can demonstrate their skills.

✨Tip Number 4

Don’t forget to follow up after your interview! A quick thank-you email can go a long way. It shows your enthusiasm for the role and keeps you fresh in the interviewer's mind. Plus, it’s a great chance to reiterate why you’re a perfect fit!

We think you need these skills to ace Senior Data Scientist II

Python Programming
OpenAI APIs
Prompt Engineering
Machine Learning Fundamentals
Natural Language Processing (NLP)
Feature Engineering
Databricks
Spark
Delta Lake
SQL
AWS Services (S3, Lambda)
Data Automation
Data Quality Assurance
Root Cause Analysis
End-to-End Solution Design

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!

Tailor Your Application: Don’t just send a generic CV! Tailor your application to reflect the specific responsibilities and requirements mentioned in the job description. This shows us that you’re genuinely interested in the role.

Be Clear and Concise: When writing your application, keep it clear and concise. We appreciate straightforward communication, so make sure your points are easy to understand and relevant to the role.

Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates!

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 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 projects where you've designed and deployed machine learning models. Be ready to explain your thought process, the challenges you faced, and how your solutions made a measurable impact.

✨Understand the Business Impact

Since this role involves working across various business functions, think about how your data science work can drive decisions in Product, Sales, or Marketing. Be prepared to discuss how you would define KPIs and connect different datasets to provide actionable insights.

✨Engage with Stakeholders

Demonstrate your ability to communicate effectively with non-technical stakeholders. Prepare examples of how you've collaborated with cross-functional teams to deliver solutions that meet their needs and how you’ve handled feedback during the project lifecycle.

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