Data Scientist – GenAI & AI Engineering at Experian

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

26 Apr, 26

Salary

0.0

Posted On

26 Jan, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Python Programming, Experimentation, AI Engineering, Problem Framing, Success Metrics, Error Analysis, Collaboration, Communication, Software Engineering, Cloud Services, Containerized Environments, Technical Explanation, Exploration, Curiosity

Industry

Information Services

Description

Company Description 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. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com. Job Description Data Scientist – GenAI & AI Engineering 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. Who is a GenAI CoE Data Scientist? This is a mid-level, hybrid 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 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 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 are curious, reflective, and thoughtful in your approach, comfortable challenging your own assumptions and engaging constructively with the ideas and work of others. 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 working with product managers, engineers, or other team members in a collaborative setting. Experience explaining technical concepts or analysis to non-technical partners. Additional Information Benefits package includes: 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. Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's people first approach is award-winning; World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ in 24 countries, and Glassdoor Best Places to Work 2024 to name a few. Check out Experian Life on social or our Careers Site to understand why. 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. #LI-Hybrid #LI-ST1 Internal Grade D/EB8 Experian Careers - Creating a better tomorrow together Find out what its like to work for Experian by clicking here Employee Status: Regular Role Type: Hybrid Department: Analytics Schedule: Full Time

Responsibilities

The Data Scientist will work with product, engineering, and business teams to clarify problem statements and design experiments to evaluate Generative AI systems. They will also communicate results and refine solutions using modern development practices.