Senior Data Scientist

Intuit's Consumer Group is committed to building tools and services that improve our members' financial journeys. At the heart of this mission, the Fast Money & Lending team is developing innovative solutions to empower customers to confidently access their tax refunds, obtain a line of credit and diversify their portfolio.

The team is seeking a Sr. Staff Data Scientist to serve as an analytical leader & strategic thought partner across our fast money & lending products - spanning refund advance, refund transfer, 5 Days Early & line of credit. 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.

Responsibilities

* Set strategy across initiatives:
Set strategy across the fast money & lending business to evaluate the customer lifecycle end to end.

* 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, and quasi-experimental designs) and applying causal inference (Propensity Score, DiD, Synthetic Control where A/B testing capability 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 & fast money 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.

* 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,banking,investing) 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 causal inference, customer segmentation, and experimentation design, with the judgment to balance statistical rigor and business considerations.

* Exposure to light weight Machine Learning in terms of being able to build offline classification & regression models to inform business decisions.

* 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.

* Ability to use AI native tools to plan, implement and synthesize analyses across a variety of use cases ranging from…