Qualifications
A minimum of 7 years in credit risk analytics, data science, or advanced analytics, particularly within non-prime or near-prime lending sectors.Hands-on experience with modeling using alternative data sources.Strong proficiency in Python, including libraries such as Pandas, NumPy, scikit-learn, and XGBoost/LightGBM for feature engineering and analysis.Advanced SQL skills with experience in handling complex and imperfect datasets.Understanding of non-prime risk dynamics, including thin-file consumers, volatility, fraud risk, and early-default behaviors.Experience with model evaluation metrics such as AUC, KS, lift, bad-rate curves, stability, and PSI.Ability to engage with clients and translate analytics into executable strategies.Capability to communicate complex models in straightforward business terms.A background in financial services, alternative lending, FinTech, or specialty finance.Familiarity with AFS data sources including Clarity, FactorTrust, MicroBilt, and specialty bureaus.Understanding of model governance and explainability.
About the job
Join Experian as a seasoned Senior Data Scientist within our Alternative Financial Services (AFS) division, focusing on the non-prime and near-prime lending sectors. In this role, you will craft tailored analytics, develop credit strategies, and create machine learning models leveraging both conventional and alternative data sources. This client-facing position demands a robust technical skill set and the capability to translate intricate analyses into actionable insights. You will report directly to the VP of Analytics Product Build, Innovation, and Scores.
In this exciting role, you will have the opportunity to:
- Lead bespoke analytics and modeling projects from inception to delivery and ongoing support.
- Create credit strategies and machine learning models for various applications, including underwriting, line assignment, pricing, early warning systems, and collections.
- Engineer features using alternative, transactional, and bureau data, focusing on metrics such as recency, frequency, volatility, trends, and behavioral indicators.
- Assess and incorporate third-party alternative data sources, including sub-prime bureaus, cash-flow data, telecom, utility, and specialty datasets.
- Collaborate with clients to devise comprehensive credit strategies that optimize approvals, mitigate losses, enhance efficiency, and improve customer experiences.
- Deliver concise, executive-ready insights, documentation, and strategic recommendations.
- Present findings directly to risk management leaders, analytics teams, and senior client partners.
- Support model implementation, monitoring, stability analysis, and ongoing enhancements.
- Engage cross-functionally with Product, Engineering, and Sales teams to ensure alignment of custom solutions with broader AFS capabilities.
About Experian
Experian is a global leader in data and technology, dedicated to creating opportunities for individuals and businesses worldwide. We are at the forefront of redefining lending practices, combating fraud, simplifying healthcare, formulating marketing solutions, and providing deeper insights into the automotive sector, all through our unique blend of data, analytics, and software solutions. We empower millions to achieve their financial aspirations while helping them save time and money.Operating across diverse markets including financial services, healthcare, automotive, agribusiness, and insurance, we are committed to investing in people and cutting-edge technologies to harness the full potential of data. As a proud member of the FTSE 100 Index, listed on the London Stock Exchange (EXPN), we employ over 22,500 professionals across 32 countries. Our corporate headquarters is located in Dublin, Ireland. Discover more about us at experianplc.com.
