Executive Director, Data Science (Risk Analytics)

About the role

Join a team where advanced analytics, strong data foundations, and practical decisioning come together to improve outcomes for customers and the firm. You will lead high-impact data science initiatives that strengthen credit and fraud risk performance through better data, better models, and better insights. This role offers the opportunity to set a multi-year vision, build new capabilities, and scale products that directly influence senior decision-making. You will partner closely with leaders and stakeholders to turn ambiguous questions into measurable business outcomes.

Job responsibilities

• Lead and develop a high-performing data science team through clear direction, coaching, and a culture of high standards, curiosity, and continuous learning
• Define and execute a multi-year vision and roadmap for evergreen data assets, decisioning capabilities, and scalable analytics products that improve credit and fraud risk performance
• Expand the coverage, quality, and utility of key data assets (for example, income-related data) to support risk decisions and insights
• Advance data mining and modeling across structured and unstructured data to identify actionable insights and early indicators of consumer and small business stress
• Lead generative artificial intelligence–enabled innovation across the data science lifecycle (for example, weak-signal discovery, entity and merchant enrichment, sequence understanding, and unstructured-to-structured transformation)
• Partner with cross-functional stakeholders and risk leadership to prioritize opportunities, define success metrics, and translate business questions into analytical solutions
• Deliver executive-ready narratives that clearly communicate insights, recommendations, tradeoffs, and expected business impact
• Drive execution in a fast-paced environment by aligning stakeholders, prioritizing work across initiatives, and delivering against roadmap milestones

Required Qualifications, Capabilities, And Skills

• Master's degree in a quantitative field (for example, computer science, statistics, mathematics, physics, or related discipline)
• Proven experience leading and developing data science teams, including coaching, performance management, and team culture
• Demonstrated ability to deliver production-grade, data-driven solutions to complex business problems
• Strong expertise in consumer financial services and applying analytics to risk decisioning (including credit and fraud)
• Deep knowledge of statistical modeling and data mining methods across structured and unstructured data
• Strong programming capability in Python and SQL (and/or comparable analytics languages) and experience working with large-scale data
• Strategic and commercial mindset: ability to frame ambiguous problems, define clear success metrics, and prioritize high-impact work
• Strong stakeholder management skills and ability to influence senior leaders through sound judgment and crisp storytelling
• Excellent written and verbal communication skills for technical and non-technical audiences

Preferred Qualifications, Capabilities, And Skills

• Doctoral degree in a quantitative field
• Experience building and scaling analytics “data products” used by multiple teams or functions
• Hands-on experience applying generative artificial intelligence techniques to analytics workflows (for example, enrichment, classification, or unstructured text processing)
• Experience improving transaction data quality, categorization, and explainability for downstream analytics or decisioning
• Experience partnering with model risk management, governance, and control functions to support responsible deployment
• Track record of delivering executive-level narratives and decision materials tied to measurable outcomes