Sr. Staff Data Scientist, Lending

Responsibilities

• Set strategy across initiatives: Turn QuickBooks Capital's business strategy into analytical problems across multiple initiatives (Marketplace and partnerships/externalization), iteratively self-generating and validating hypotheses to create actionable insights and recommendations that inform decision-making at the Business Unit level.
• Influence senior leadership: Combine insights, business acumen, strategic considerations, and industry-wide learnings to influence cross-functional leaders up to the VP level; act as the connective tissue across Product, Marketing, Engineering, and Design.
• Advance the science: Identify new ML and causal inference methodologies and external trends, adapt them to lending use cases, and create shareable frameworks that enable adoption across the BU — with clarity on when and how each methodology should be used to drive business value.
• Lead experimentation at scale: Drive an iterative experimentation culture across the team — designing complex experiments (A/B/n, painted-door, bandits, geo/holdout, and quasi-experimental designs) and applying causal inference (Propensity Score, DiD, Synthetic Control, with growing depth in Doubly Robust Estimation and Instrumental Variables) where A/B testing is limited.
• Build durable segmentation & customer understanding: Identify key patterns in customer behavior by connecting insights across a portfolio of experiments and analyses; create durable customer segmentation strategies that enhance targeting, positioning, and the application experience.
• Shape the AI-native roadmap: Co-create the analytics/AI strategy for lending in partnership with cross-functional teams; guide phased testing and rollout with the right measurement, safety, risk, and ethical considerations; connect model performance metrics to customer and business outcomes.
• Drive build/buy and tooling decisions: Identify the biggest pain points in analytics workflows and serve as a thought partner on build/buy decisions; champion reusable, scalable analytics tools that eliminate redundant effort across the team.
• Raise the bar & develop talent: Mentor and elevate Data Scientists across the team, set scientific standards and best practices, contribute to calibrations and hiring, and scale yourself through delegation while remaining hands-on in the highest-leverage areas.

Qualifications

• 9+ years of experience in data science and analytics, with a track record of driving strategy and impact across multiple initiatives or business units; fintech experience (lending, credit cards, or marketplaces) strongly preferred.
• Demonstrated ability to apply first-principles thinking to translate ambiguous business strategy into analytical problems at the business-unit level.
• Proven success designing and interpreting complex experiments well beyond traditional A/B testing, and applying causal inference where experimentation is constrained.
• Deep expertise in predictive/prescriptive modeling, causal inference, customer segmentation, and experimentation design, with the judgment to balance statistical rigor and business considerations.
• Experience creating reusable frameworks, methodologies, and toolkits that are adopted by a broader analytics community.
• Exceptional communication and stakeholder-influence skills, with a demonstrated ability to influence Director- and VP-level leaders across business and technical teams.
• Ability to navigate ambiguity with minimal guidance, make fast data-driven decisions (one-way vs. two-way door), and operate effectively in a fast-paced, dynamic environment.
• BS or MS in Statistics, Mathematics, Operations Research, Computer Science, Engineering, Econometrics, or a related field (advanced degree preferred).