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Job description
Intuit is hiring a Senior Staff Data Scientist to support the Credit Karma Engagement workstream in Charlotte, North Carolina. In this onsite role, you will help shape the analytics vision for engagement and lifecycle initiatives, using experimentation and causal inference to improve long-term member retention.
What you’ll do
Set the data science strategy across Credit Karma engagement and lifecycle product initiatives, evaluating the member lifecycle end to end from activation and habit formation through retention, churn prevention, and reactivation.
Bring together analytics insights, business judgment, strategic considerations, and industry learnings to influence cross-functional leaders up to the VP level, serving as a connective point across Product, Marketing, Engineering, and Design .
Research and apply new ML and causal inference approaches, adapting external trends to engagement, lifecycle, and churn-prevention use cases while creating shareable frameworks that enable broader adoption within the business unit.
Build an iterative experimentation culture by designing complex studies including A/B/n , painted-door , bandits , and quasi-experimental designs , and by applying causal inference methods such as Propensity Score , DiD , and Synthetic Control when A/B testing is limited.
Connect learnings across a portfolio of experiments and analyses to identify patterns in member behavior, and develop durable segmentation strategies that strengthen targeting, personalization, and the in-product experience.
Partner with cross-functional teams to co-create the analytics and AI strategy for engagement and lifecycle, guiding phased testing and rollout with appropriate measurement, safety, risk, and ethical considerations while tying model performance metrics to member and business outcomes.
Mentor and elevate Data Scientists by setting scientific standards and best practices, contributing to calibrations and hiring, and scaling impact through delegation while staying hands-on in the highest-leverage areas.
Minimum qualifications
9+ years of experience in data science and analytics, with a demonstrated track record leading strategy and delivering impact across multiple initiatives or business units; experience in consumer product engagement, retention, or growth strongly preferred, with fintech experience a plus.
Experience in consumer platforms with membership-based or multi-product ecosystems where personalization and cross-product engagement drive long-term retention (preferred).
Ability to apply first-principles thinking to translate ambiguous business strategy into analytics problems at the business-unit level.
Proven ability to design and interpret complex experiments beyond traditional A/B testing and to apply causal inference when experimentation is constrained.
Deep expertise in causal inference, customer segmentation, and experimentation design, with judgment to balance statistical rigor and business considerations.
Experience with lightweight Machine Learning, including building offline classification and regression models to inform business decisions.
Experience creating reusable frameworks, methodologies, and toolkits adopted by a broader analytics community.
Strong communication and stakeholder influence, including the ability to influence Director- and VP-level leaders across business and technical groups.
Ability to work effectively in ambiguity with minimal guidance, make fast data-driven decisions (one-way vs. two-way door), and operate in a fast-paced environment.
Ability to use AI-native tools to plan, implement, and synthesize analyses across experiment readouts, quasi-experimental methodology, retention and churn deep dives, and measurement of feature launch success.
BS or MS in Statistics, Mathematics, Operations Research, Computer Science, Engineering, Econometrics, or a related field (advanced degree preferred).
Technologies
Machine Learning
Offline classification & regression models
AI-native tools
Propensity Score
DiD
Synthetic Control
A/B/n
Painted-door
Bandits
Quasi-experimental designs
Compensation
Intuit offers a competitive compensation package with a pay-for-performance rewards approach. This role may be eligible for a cash bonus, equity rewards, and benefits in accordance with applicable plans. Pay is based on job-related knowledge, skills, experience, and work location, and Intuit conducts regular pay comparisons across categories of ethnicity and gender. The expected base pay range for this position is USD 210,500 - 284,500 per year (noted with an expected base pay range shown as Oakland in the posting).
Location: Charlotte, NC (onsite)
Salary: USD 210,500 - 284,500 per yearly
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Worksite address
charlotte, NC, 28245, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.