Data Scientist - Credit Scorecard Development - London (Hybrid) - £700p/d

• Independently prepare complex datasets, run exploratory analysis, and build predictive models, risk scorecards, and decisioning tools
• Drive commercial product innovation - identify market gaps, prototype algorithms, take concepts to market-ready products
• Design and optimise data pipelines integrating large volumes of disparate commercial data
• Translate data assets into actionable business strategy and long-term analytics roadmap
• Apply advanced statistical/ML methods to uncover patterns in high-dimensional data
• Solve cross-domain problems (commercial risk, business failure, fraud detection) with engineering, product, and strategy teams
• Communicate complex findings clearly to technical and non-technical stakeholders
• Maintain data quality, governance, validation, and regulatory compliance standards
• Stay current with cloud capabilities (primarily GCP) and modern analytical tooling
• Mentor junior data scientists and lead code/quality reviews

Hands-on Scorecard Build History: Must have personally built and deployed at least 2 end-to-end credit scorecards (consumer or commercial). We are looking for someone who writes the code and build the bins rather than a manager or analyst who only reviews the output.

Hands-On Python Execution: Advanced, fluent Python coder.

Must be comfortable writing custom data transformation functions and debugging logic live without relying on template scripts or AI coders.

Pragmatic Data Engineering: Strong SQL skills to ingest, merge, and clean messy, high-dimensional datasets independently in cloud environments (GCP/BigQuery preferred)., * STEM degree (Master’s preferred)

• Proven experience working in a Data Scientist or quantitative modelling role
• Extensive experience with commercial data assets (eg business registry, trade credit, or bureau data)
• Strong commercial data interpretation, auditing, and validation skills
• Python and SQL (Unix/Shell Scripting a plus)
• Foundational credit risk modelling/scorecard life cycle knowledge (sampling, WoE, scaling)
• Git and CI/CD workflow experience
• Hands-on cloud development experience (GCP preferred)
• Exposure to ML methods (XGBoost, Random Forests, Neural Networks) and traditional stats (Logistic Regression)
• Awareness of data security, governance, and model risk management standards

Nice to Have

• UK commercial lending/regulatory knowledge (PRA/FCA, Consumer Duty, Basel 3.1)
• Experience building/validating commercial credit scorecards
• Exposure to Open Banking, transactional data, bureau feeds, ESG data
• Track record of independently pitching and delivering analytical products

Global Financial Services Client now require a Data Scientist to join a high-performing Product Analytics & Innovation team building market-leading credit risk scores, predictive models, and AI-driven commercial data products on modern cloud infrastructure.