Sr. Data Scientist, Lending

Position: Sr. Staff Data Scientist, Lending
** Overview*
* Intuit's  
** Global Business Solutions Group (GBSG)*
* ** is committed to building tools and services that significantly enhance the ability of small and medium-sized businesses to manage cash flow. At the heart of this mission, the*
* ** Quick Books Capital*
* ** team is developing innovative solutions that empower customers to confidently access the right loan offerings with greater ease.*
* The  
** Lending Data Science*
* ** team is seeking a*
* ** Sr. Staff Data Scientist*
* ** to serve as the analytical leader and strategic thought partner across our lending portfolio - spanning the*
* ** Lending Marketplace**   **(connecting small and medium businesses with the most suitable loans) and our*
* ** partnerships & externalization*
* ** efforts (e.g., partnering with organizations like Amazon to deliver personalized loan offers at scale). This is a high-impact, cross-initiative role where you will set the analytics vision, raise the scientific bar across the team, and influence product, marketing, and lending strategy at the Business Unit level.*
* As a  
** Sr. Staff Data Scientist,
** you operate as a technical leader and domain expert  
** across multiple teams and initiatives**  **. You apply first-principles thinking to turn business strategy into analytical problems, build reusable frameworks and methodologies that the broader analytics community adopts, and influence senior cross-functional leaders (Directors and VPs) with insights grounded in deep customer understanding, business acumen, and industry-wide context.*
* ** Responsibilities*
* +  
** Set strategy across initiatives:*
* ** Turn Quick Books 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*
* We're looking for a curious, proactive, and influential data science leader with a passion for fintech.

+  
** 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,…