National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Lead Data Scientist - Model Risk Management

Experian
London
1 month ago
Create job alert

Job Description

Our Experian Software Solution's Analytics Services Team supports analytic and generative AI products for decisioning, analytics, and fraud and identity globally.

As a Lead Data Scientist, you will use your coding expertise (Python, SAS), model risk management and Gen AI knowledge and experience, and analytic consulting skills to lead client and internal engagements for Experian's new global product launch and early client success efforts.

Responsibilities:

Collaborate with Engineering and Data Science teams in the design and implementation of Machine Learning, Dashboarding, Ad Hoc Analysis and AI applications in a cloud-native big data platform. Partner with Leaders, Analytic Consultants, Engineers, Account Executives, Product Managers, and external partners to bring new innovative solutions to market that provide impact to Experian's broad client base. Lead client analytic consulting engagements with financial services clients, including pre-sales and demos, training, and client success activities to maximize client value. Leverage Gen AI and model development tools to create and maintain new model document templates to help clients meet Model Risk Management regulatory requirements. Stay informed about regulatory changes, technological advancements, and model risk management processes and controls to ensure the technology stack meets all compliance requirements. Research and integrate new data assets from different sources into Experian's ML and AI platform. Develop and assess analytic tools developed internally and externally. Gather feedback from internal and external clients to guide new product development, feature prioritisation, and product evolution of tools and capabilities supported by the Ascend Platform.


Qualifications

Data science background with development expertise in Python (preferred) or SAS Experience developing models and creating model documentation for Model Risk Management teams in credit or fraud risk and decisioning Understand model risk management regulatory environment and governance requirements for model documentation, validation, and monitoring Experience building analytical tools and providing product and analytic requirements in a regulatory environment A track record for managing complex analytical technology projects  The ability to present to all levels of management within Experian and clients


Additional Information

Benefits package includes:

Hybrid working 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 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, engagement, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's people first approach is award-winning; Great Place To Work™ in 24 countries, FORTUNE Best Companies to work and Glassdoor Best Places to Work (globally 4.4 Stars) 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.

Grade:C / EB7

#LI-DS1 #LI-Hybrid

Experian Careers - Creating a better tomorrow together

Find out what its like to work for Experian by clicking here

Related Jobs

View all jobs

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Jobs Skills Radar 2026: Emerging Tools, Frameworks & Platforms to Learn Now

Machine learning is no longer confined to academic research—it's embedded in how UK companies detect fraud, recommend content, automate processes & forecast risk. But with model complexity rising and LLMs transforming workflows, employers are demanding new skills from machine learning professionals. Welcome to the Machine Learning Jobs Skills Radar 2026—your annual guide to the top languages, frameworks, platforms & tools shaping machine learning roles in the UK. Whether you're an aspiring ML engineer or a mid-career data scientist, this radar shows what to learn now to stay job-ready in 2026.

How to Find Hidden Machine Learning Jobs in the UK Using Professional Bodies like BCS, Turing Society & More

Machine learning (ML) continues to transform sectors across the UK—from fintech and retail to healthtech and autonomous systems. But while the demand for ML engineers, researchers, and applied scientists is growing, many of the best opportunities are never posted on traditional job boards. So, where do you find them? The answer lies in professional bodies, academic-industry networks, and tight-knit ML communities. In this guide, we’ll show you how to uncover hidden machine learning jobs in the UK by engaging with groups like the BCS (The Chartered Institute for IT), Turing Society, Alan Turing Institute, and others. We’ll explore how to use member directories, CPD events, SIGs (Special Interest Groups), and community projects to build connections, gain early access to job leads, and raise your professional profile in the ML ecosystem.

How to Get a Better Machine Learning Job After a Lay-Off or Redundancy

Redundancy in machine learning can feel especially frustrating when your role was technically advanced, strategically important, or AI-facing. But the UK still has strong demand for machine learning professionals across fintech, healthtech, retail, cybersecurity, autonomous systems, and generative AI. Whether you're a research-oriented ML engineer, production-focused MLOps developer, or applied scientist, this guide is designed to help you bounce back from redundancy and find a better opportunity that suits your goals.