Lead Data Scientist

Lead Data Scientist – Financial Services

About Us

Our client is a leading financial services organisation embarking on a major data and analytics transformation programme. They are investing heavily in advanced analytics, predictive modelling, and data-driven products to unlock the value of a rich and extensive data estate. This is a unique opportunity to join a high-impact team focused on building innovative solutions that will shape the future of the business.

The Role

We're looking for a Lead Data Scientist to drive the development of predictive models and analytical products in a highly regulated environment. Working closely with senior leadership, you'll take ownership of the full data science lifecycle—from data exploration and feature engineering through to model deployment, monitoring, and governance. This role is ideal for someone who enjoys solving complex business problems, building production-grade models, and delivering tangible commercial impact.

Key Responsibilities:

• Develop and deploy predictive models to support commercial, risk, and strategic decision-making.
• Build and maintain modelling datasets using large-scale structured data sources.
• Lead exploratory data analysis, feature engineering, model selection, validation, and performance monitoring.
• Design and execute forecasting, simulation, and scenario analysis to support business planning.
• Ensure models are robust, explainable, and compliant with governance and regulatory requirements.
• Implement reproducible, version-controlled data science workflows and best practices.
• Collaborate with data engineering and business stakeholders to deliver scalable data products.
• Evaluate and optimise machine learning models, balancing performance, transparency, and business value.

About You:

• Strong experience developing predictive models within financial services or another highly regulated environment.
• Advanced Python skills (Pandas, NumPy, Scikit-learn) and strong SQL capabilities.
• Experience working with Snowflake or similar cloud-based data platforms.
• Strong background in exploratory data analysis, feature engineering, and model validation.
• Experience developing production-ready machine learning solutions and monitoring frameworks.
• Understanding of model governance, auditability, and regulatory requirements.
• Knowledge of credit risk, forecasting, scorecards, probability models, or related analytical techniques would be highly advantageous.
• Experience using Git and version-controlled development practices.
• Excellent communication skills with the ability to explain complex analytical concepts to senior stakeholders.

Why Join?

This is an opportunity to join a highly visible, strategically important team where you'll have significant influence over the direction of analytics and data products. You'll work on complex, high-value challenges, collaborate directly with senior decision-makers, and help build capabilities that will drive long-term business growth.

Employment Type: Full-time, Permanent