Senior Staff Data Scientist, Money

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 experiment readouts, quasi experimental methodology, revenue deep dives & measuring the success of product launches.

• BS or MS in Statistics, Mathematics, Operations Research, Computer Science, Engineering, Econometrics, or a related field (advanced degree preferred).

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is: Oakland $210,500 - $284,500