Executive Director, Data Science (Risk Analytics)

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 summary

As an Executive Director, Data Science in the Chase 360 team within the consumer risk organization, you will lead a team of data scientists and analytics professionals to deliver insights and decisioning capabilities that materially improve credit and fraud risk outcomes.

You will shape and execute a roadmap for durable ("evergreen") data assets and scalable analytics products, from discovery through production.

You will work across functions to identify the most important business problems, define success metrics, and translate opportunities into actionable analytical solutions.

You will communicate clearly and credibly with both technical teams and senior leaders, balancing tradeoffs to drive timely decisions.

You will be expected to challenge existing paradigms, raise quality and explainability standards, and improve how data becomes insight at scale.

The work spans structured and unstructured data, risk monitoring, and enterprise data product thinking-so you can move from strategy to execution while keeping teams aligned and motivated.

You will also identify where generative artificial intelligence can responsibly accelerate the analytics lifecycle and improve analyst productivity.

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


* Reimagine end-to-end transaction categorization to improve quality, explainability, scalability, and speed to availability for downstream risk use cases


* 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 succ...