Lead Data Scientist - Credit Modelling & Data Products

Lead Data Scientist - Credit Modelling & Data Products

My client is building a next-generation data and analytics capability using large-scale financial datasets spanning millions of records. Their goal is to transform complex data into predictive insights, industry intelligence, and innovative data products that create real business value.

This is a unique opportunity for an experienced Lead Data Scientist to join a small, high-impact innovation team, working directly with executive leadership. You will take ownership of the most challenging technical problems, from data modelling and forecasting through to production deployment of predictive analytics solutions in a regulated financial services environment.

As Lead Data Scientist, you will be responsible for designing, building, and governing predictive models that support data-driven products and strategic decision-making. You will work closely with engineering and product teams to transform raw data into robust, auditable, and commercially valuable solutions.

Key Responsibilities

• Partner with data engineering teams to extract, cleanse, and consolidate large customer datasets into modelling-ready environments.
• Develop predictive models for use within regulated financial services and credit risk environments.
• Own the full data science life cycle, including:
• Exploratory Data Analysis (EDA)
• Feature engineering and selection
• Model development and validation
• Calibration and performance monitoring
• Build forecasting models, simulations, and stress-testing frameworks to support risk and product decisions.
• Maintain fully auditable, version-controlled, and reproducible modelling workflows.
• Collaborate with product stakeholders to rapidly transform concepts into scalable data products.
• Contribute to model governance frameworks and ensure compliance with regulatory requirements.

Skills & Experience

Technical Expertise

• Strong proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL.
• Hands-on experience with Snowflake or similar cloud-based data warehouse platforms.
• Experience using Git and reproducible development practices.
• Strong understanding of data pipelines, data quality, and analytics engineering principles.

Credit Modelling & Predictive Analytics

• Proven experience conducting rigorous exploratory data analysis and feature engineering.
• Experience building predictive models in regulated financial services environments, ideally within:
• Retail banking
• Commercial banking
• Asset securitisation
• Credit management
• Expertise developing and deploying credit risk models, including:
• Probability of Default (PD) models
• Scorecards
• Risk segmentation models
• Experience evaluating and implementing challenger models such as XGBoost while balancing explainability and regulatory requirements.
• Strong understanding of model performance metrics including AUC, Gini, KS, calibration, and business impact measurement.
• Experience deploying production-ready models with monitoring, retraining triggers, and controls against issues such as target leakage.

Governance & Regulatory Knowledge

• Experience operating within model risk governance frameworks, including documentation, validation, and audit requirements.
• Strong understanding of GDPR and automated decision-making considerations.
• Awareness of emerging AI regulations, including the EU AI Act and related governance requirements.
• Knowledge of security-by-design principles when working with sensitive financial and personal data.

Why Join Us?

• Opportunity to shape and build a new data products capability from the ground up.
• Direct exposure to senior leadership and strategic decision-making.
• Work on complex, high-value datasets and industry-leading predictive analytics challenges.
• Join a collaborative environment that values innovation, ownership, and impact.
• Competitive salary and benefits package with flexible hybrid working.

If you're passionate about turning complex financial data into meaningful products and insights, we'd love to hear from you.

Due to the volume of applications received for positions, it will not be possible to respond to all applications and only applicants who are considered suitable for interview will be contacted.

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