Data Scientist – GenAI & AI Engineering

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments. We invest in people and new advanced technologies to unlock the power of data.

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 role for a data scientist who enjoys hands‑on work and wants to grow into AI engineering. You will 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:

• Work with product, engineering, and business teams to turn fuzzy ideas into clear problem statements, assumptions, and success metrics.
• 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.

Qualifications:

• Experience working as a data scientist (or in a similar role), applied machine learning, and Python programming.
• Comfortable working with incomplete information, and enjoy figuring things out through exploration and experimentation.
• Keen to develop broader skills across AI engineering and product‑focused delivery.
• Curious, reflective, and thoughtful in your approach, comfortable challenging your own assumptions and engaging constructively with the ideas and work of others.
• Think beyond your scope: 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.
• Understanding of how companies deploy or run AI systems in practice through cloud services or containerised environments.
• Experience working with product managers, engineers, or other team members in a collaborative setting.
• Experience explaining technical concepts or analysis to non‑technical partners.

Benefits:

• Hybrid working – 2 days in the office.
• 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.

Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.