Lead Data Scientist

Overview

As the lead Data Scientist, you will establish and grow BFS’s analytics capability by delivering predictive models and advanced analytics. You’ll shape standards, tooling and best practices for a scalable Data Science function in the Azure Databricks Lakehouse. You’ll tackle high-impact business problems across credit risk, pricing and retention, translating data insights into strategic decisions. This role offers a chance to lead and mentor a team while partnering with stakeholders to drive measurable value and technical excellence.

Pay / Benefits

• 25 days’ holiday plus bank holidays
• Hybrid working
• Private healthcare for you and your family
• Company pension scheme
• Flexible benefits (gym membership, tech, health assessments)
• Online wellbeing centre

Responsibilities

• Design, develop and deploy predictive and statistical models for strategic and operational decision-making
• Deliver Data Science solutions across use cases including customer attrition, credit risk, likelihood-to-pay and pricing optimization
• Apply ML and statistical techniques to solve business challenges and create measurable value
• Evaluate and improve model performance, ensuring scalability and operability
• Explore large datasets to identify trends and opportunities
• Translate business problems into analytical approaches and Data Science solutions
• Communicate findings clearly to technical and non-technical audiences
• Partner with stakeholders to define success metrics and assess impact
• Establish standards, frameworks and best practices for Data Science and ML across the organisation
• Define model development, validation, deployment and lifecycle management approaches
• Develop scalable Data Science and MLOps processes within Azure Databricks Lakehouse
• Collaborate with Data Engineering, Data Architecture and Data Governance to align with data standards
• Support tooling for model versioning, deployment, monitoring and performance management
• Explain models to non-technical stakeholders and articulate business impact
• Act as subject-matter expert for Data Science and predictive analytics
• Work with departments to prioritise opportunities for advanced analytics
• Mentor data scientists and data professionals in advanced analytical techniques
• Support Head of Data in defining the Data Science roadmap and growth

Key requirements

• Significant experience in Data Science, ML or advanced analytics
• Proven ability to develop and deploy predictive models with measurable outcomes
• Knowledge of statistical modelling and ML techniques and evaluation methods
• Advanced Python and SQL skills for Data Science and model development
• Experience with Azure Databricks or similar cloud analytics platforms
• Proficiency in MLOps including deployment, version control, monitoring and lifecycle management
• Ability to translate business challenges into practical Data Science solutions and communicate with non-technical stakeholders
• Excellent stakeholder management and ability to lead complex initiatives independently

• Stakeholder management
• Independent, leadership-oriented work style
• Ability to communicate insights to non-technical audiences
• Python
• SQL
• Azure Databricks Lakehouse

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