Data Scientist - GenAI & AI Engineering-4 month secondment

Experian Information Solutions, Inc.
London, United Kingdom
5 days ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Working hours
Regular working hours

Tech stack

Artificial Intelligence Python (Programming Language) Machine Learning Object-Oriented Software Development Cloud Services Software Engineering Generative AI Software Version Control

Job description

The Generative AI Centre of Expertise (GenAI CoE) at Experian helps teams across Experian’s UK business. It improves products using Generative AI, machine learning, and automation. The centre has a focus on responsible, measurable impact., This is a mid-level, hybrid secondment role for a data scientist who enjoys hands-on work and wants to grow into AI engineering. You’ll report into the Head of Machine Learning and work across two connected areas:

  • Experimentation and evaluation (data science): framing problems, designing experiments, defining success metrics, analysing results, and understanding model/system behaviour in product contexts
  • AI engineering: build GenAI systems (prototypes through to production-ready components), supported by experienced colleagues

A big part of the job is choosing the right approach - when GenAI is valuable, and when simpler analytics or ML is the better answer.

What you’ll do

  • You will work with product, engineering, and business teams to turn fuzzy ideas into clear problem statements, assumptions, and success metrics
  • You will design and run experiments to evaluate GenAI systems, including baseline comparisons, error analysis, and understanding failure modes
  • Help refine GenAI solutions, using modern development practices and AI-assisted coding tools to iterate quickly
  • Communicate results, including trade-offs, limitations, and recommendations for what to do next
  • Share insights with the team and spend ~10% of your time on learning and knowledge sharing

Requirements

You have experience working as a data scientist (or in a similar role), applied machine learning, and Python programming.

  • You are comfortable working with incomplete information, and enjoy figuring things out through exploration and experimentation.
  • You are keen to develop broader skills across AI engineering and product-focused delivery.
  • You think beyond your scope: you join up product, data, and engineering context to spot issues early and improve decisions.

It would be great if you also have

  • Exposure to software engineering practices such as version control, testing, or object-oriented programming.
  • You will understand how companies deploy or run AI systems in practice through cloud services or containerised environments.
  • Experience explaining technical concepts or analysis to non-technical partners

Benefits & conditions

Benefits package includes:

  • Hybrid working - 40% office based
  • Great compensation package and discretionary bonus plan
  • Core benefits include pension, bupa healthcare, sharesave scheme and more!
  • 25 days annual leave with 8 bank holidays and 3 volunteering days. You can also purchase additional annual leave.

Our uniqueness is that we celebrate yours. Experian’s people first, inclusive and purpose driven culture is multi award-winning; World’s Best Workplaces 2025 (Fortune Global Top 25), Great Place To Work in 26 countries to name a few. Check out Experian Life on social or explore our Careers Site to understand why. Experian is also proud to be an Equal Opportunity and Affirmative Action employer. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

About the company

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more. Experian invests in people and new advanced technologies to unlock the power of data. We have an amazing team of 25,200 people in 32 countries.

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