Credit Data Scientist

About the job

Role purpose As a Credit Data Scientist, you’ll use data, feature engineering and experimentation to improve credit decisioning and portfolio performance across our lending products and markets. You’ll work end-to-end from data exploration through to production-aligned features, monitoring and impact measurement. Key responsibilities Analyse customer, bureau, transactional and repayment data to identify drivers of risk, loss, approval rates and customer outcomes. Build and iterate credit risk features and model inputs (behavioural signals, affordability proxies, stability-tested transformations), partnering closely with senior modellers and engineering. Contribute to development and improvement of predictive models using modern machine learning approaches, with a focus on robustness, stability and deployability. Design, run and evaluate credit policy experiments (cut-offs, limits, pricing/risk trade-offs, segment strategies), including post-implementation reviews. Develop monitoring for model/policy performance and feature health (drift, stability, segment performance, data quality checks). Support portfolio analytics: vintage analysis, roll-rates, migration, early warning indicators, collections funnel analytics, and loss driver deep-dives. Work with Data/Engineering to improve data definitions, quality, lineage and reproducible pipelines; document feature logic and assumptions. Contribute to governance documentation (model inputs, feature catalogues, monitoring evidence, change logs).

Requirements

• Data Science
• Python
• SQL
• Credit Risk Analysis

Qualifications

• 2-4 years in credit analytics or lending data science
• Strong Python and SQL skills
• Proficiency in Python or R for analysis and modelling

Preferred Technologies

• Data Science
• Python
• SQL
• Credit Risk Analysis

About the company

Tymex is a financial technology company that focuses on enhancing credit decision-making through data science and analytics in lending products and markets.