Staff Data Scientist - Engagement

Intuit, Inc.; Oakland (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Intuit, Inc. seeks a Staff Data Scientist to partner with the Subscriptions team, owning analytics across the member lifecycle from trial through renewal.

You will drive experimentation, segmentation, and AI/ML initiatives to improve engagement and retention, working with Product, Engineering, and Design to shape the roadmap. The role emphasizes translating ambiguous questions into structured analyses, mentoring junior data scientists, and delivering measurable business impact in a fast-paced

Qualifications

• 7+ years of data science and analytics delivering impact in a product or lifecycle-based domain.
• Strong ability to translate vague product questions into structured analyses and recommendations.
• Experience designing and interpreting experiments with causal inference for constrained testing.
• Solid understanding of customer segmentation and experimentation design with balance of rigor and business needs.
• Exposure to lightweight ML to inform business decisions.
• Experience contributing to reusable analytical frameworks or tools used by teams.
• Excellent communication and stakeholder-influence skills with senior partners.
• Ability to navigate ambiguity and make fast data-driven decisions in a fast-paced environment.
• Experience using AI-native tools to plan, implement, and synthesize analyses across use cases.

Responsibilities

• Drive analytics strategy for Subscriptions: own analytics agenda across the end-to-end member journey.
• Partner with product leadership to shape roadmap and prioritization decisions.
• Apply ML and causal inference to churn prediction, renewal optimization, and pricing experiments.
• Design and run experiments (A/B/n, quasi-experimental) to evaluate changes in member experience and outcomes.
• Build segmentation to improve targeting, personalization, and offer strategy.
• Contribute to the AI-native roadmap and connect model performance to outcomes.
• Mentor and support the team, contributing to hiring and calibration.

Skills

Subscription analytics

Experiment design

Causal inference

Segmentation

ML offline models

Cross-functional collaboration

Communication with stakeholders

Ambiguity navigation

AI-native tools

Data-driven decision making

Education

BS or MS in Statistics/Mathematics/OR/CS/Engineering/Econometrics

Job description

Intuit's Consumer Group is committed to building tools and services that improve our members' financial journeys. At the heart of this mission, the Credit Karma Engagement team builds in-product features and experiences that help members take meaningful action to improve their financial outcomes, from building credit, to saving money, to paying down debt.

The team is seeking a Staff Data Scientist to serve as an analytical partner to our Subscriptions product team, responsible for using data to improve the member experience across the subscription lifecycle, from trial and conversion through renewal and retention. This is a high-impact role where you will bring scientific rigor to product decisions, partner closely with Product and Engineering, and help shape how we measure and grow subscription value for our members.

Responsibilities

• Drive analytics strategy for Subscriptions:Own the analytics agenda for the Subscriptions product area, mapping the member journey end to end, from trial and onboarding through conversion, renewal, and cancellation, to identify the highest-leverage opportunities.
• Partner with product leadership:Combine data insights with business acumen to partner with Product, Engineering, and Design leaders in shaping roadmap and prioritization decisions.
• Apply advanced analytical methods:Apply ML and causal inference techniques to subscriptions-specific problems such as churn prediction, renewal optimization, and pricing or packaging experiments, adapting existing frameworks or building new ones as needed.
• Design and run experiments:Design and execute experiments (A/B/n, and quasi-experimental designs where testing is constrained) to evaluate changes to the member experience and quantify their impact on member and business outcomes.
• Build member segmentation:Analyze member behavior within Subscriptions to build segmentation that improves targeting, personalization, and offer strategy.
• Contribute to the AI-native roadmap:Partner with the team to identify opportunities to apply AI/ML within the subscriptions experience, help design measurement plans, and connect model performance to member and business outcomes.
• Mentor and support the team:Mentor other data scientists on best practices and experimentation rigor, and contribute to hiring and calibration as needed.

Qualifications

We're looking for a curious, proactive data scientist with a passion for driving member engagement and retention.

• 7+ years of experience in data science and analytics, with a track record of driving impact within a product area or initiative; experience with subscription, membership, or lifecycle-based products strongly preferred, fintech experience a plus.
• Ability to translate ambiguous product questions into structured analyses and actionable recommendations.
• Experience designing and interpreting experiments, with working knowledge of causal inference techniques for use when experimentation is constrained.
• Solid understanding of customer segmentation and experimentation design, with the judgment to balance statistical rigor and business considerations.
• Exposure to lightweight Machine Learning in terms of being able to build offline classification & regression models to inform business decisions.
• Experience contributing to reusable analytical frameworks, methodologies, or tools used by others on the team.
• Strong communication and stakeholder-influence skills, with the ability to work effectively with Director-level partners across business and technical teams.
• Ability to navigate ambiguity, make fast data-driven decisions, and operate effectively in a fast-paced, dynamic environment.
• Ability to use AI-native tools to plan, implement, and synthesize analyses across use cases ranging from experiment readouts to retention/churn deep dives.
• BS or MS in Statistics, Mathematics, Operations Research, Computer Science, Engineering, Econometrics, or a related field.

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.