Director of Data Science

📋 Description

• • Lead and grow a team of data scientists focused on building quantitative models to solve core business problems in credit risk, payments, churn prediction, and revenue forecasting.
• • Mentor and guide data scientists in developing, evaluating, and deploying machine learning models using Python and industry-standard tools such as dbt, Airflow, Spark, and MLflow.
• • Evangelize the data science team’s capabilities by collaborating with product, engineering, and operations teams to align model development with product roadmaps and business objectives.
• • Drive quarterly planning sessions with business stakeholders to prioritize and validate data science initiatives that deliver measurable business impact.
• • Champion the adoption of AI-assisted development and agentic workflows, including identifying practical use cases for tools like Claude Code, Cursor, GitHub Copilot, and OpenAI Codex, while ensuring adherence to privacy, validation, and quality standards.
• • Partner with the Modeling Engineer to optimize infrastructure for model research, development, and deployment, improving scalability and efficiency across the data science lifecycle.
• • Translate complex analytical findings into clear, actionable insights for commercial and executive stakeholders to inform strategic decision-making.
• • Build a high-impact data science culture rooted in accountability, data-driven outcomes, and continuous talent development.
• • Ensure all modeling efforts comply with regulatory and ethical standards, particularly in consumer financial products involving credit risk and automated decision-making.
• • Expand the team’s capacity to deliver new models across multiple product domains while maintaining rigorous standards for model performance, documentation, and reproducibility.
• • Act as a bridge between technical teams and business units to ensure data science projects are scoped, resourced, and timed to maximize alignment with company goals.
• • Stay current with advancements in AI-assisted coding, agentic systems, and data science tooling to continuously improve team productivity and model quality.
• • Oversee end-to-end model lifecycle from ideation and prototyping to production deployment and ongoing monitoring.
• • Foster cross-functional collaboration to embed data science into product development cycles and operational workflows.
• • Maintain a strong focus on customer-centric outcomes, ensuring models directly contribute to helping members build credit, avoid fees, and improve financial health.
• • Document modeling processes, assumptions, and results to ensure transparency, auditability, and knowledge sharing across the organization.
• • Evaluate and implement best practices for model governance, bias detection, and fairness in financial modeling applications.
• • Represent the data science team in executive and cross-departmental meetings to communicate progress, challenges, and strategic priorities.
• • Support recruitment and onboarding of new data science talent to scale the team effectively while preserving team culture and technical excellence.