Senior Staff Decision Science (Risk)

About the role

We are seeking an experienced Senior Staff Decision Scientist to join our Risk and Decision Science team. In this role, you will play a pivotal part in shaping the design of a new credit product, developing its risk policy and launch strategy, and proactively identifying the next opportunities to expand its scope. Your work will be central to managing financial risk, maximizing customer lifetime value (LTV), and driving long-term business growth.

What you’ll do

• Partner with the product, engineering and Legal & Compliance team to shape product strategy and define the 3–6 month risk roadmap for the domain.
• Define and implement risk policies and strategies to support the product's launch.
• Build scalable, product-level dashboards and pipelines to track product KPIs, risk exposure and loss trends that are reused across teams 
• Leverage data-driven insights and experimentation to inform policy updates, drive continuous improvement to maximize customer LTV.
• Take full ownership of the product's unit economics — setting ambitious goals and identifying the pathway to sustainable, long-term growth.

Key qualifications

• 8+ years of relevant experience, including risk/credit strategy at a financial institution or Fintech.
• A graduate degree in Statistics, Mathematics, Computer Science, or a related quantitative field.
• Advanced proficiency in SQL and data visualization, with a track record of building scalable analytics and tooling that other teams reuse.
• Excellent problem-solving skills and effectiveness in communicating complex technical concepts to non-technical stakeholders.
• Subject-matter expertise across a large risk domain (e.g., existing-user credit risk or account takeover), with a strong sense of ownership and a track record of proactively expanding scope.
• Hands-on experience applying AI/LLM tools (e.g., Claude Code) to accelerate analytics — evaluating and adopting AI tooling for the team and building automations others reuse, with sound judgment on accuracy, bias, and compliance.