Staff Data Scientist - Engagement

Intuit’s Consumer Group is focused on building tools and services that strengthen members’ financial journeys. Within this organization, the Credit Karma Engagement team creates in-product experiences that help members take meaningful actions, from building credit to saving money and paying down debt. This Staff Data Scientist role partners with the Subscriptions product team to use advanced analytics to improve the member experience across the subscription lifecycle. What you will do Lead subscriptions analytics strategy by owning the analytics agenda for Subscriptions and mapping the member journey end to end, from trial and onboarding through conversion, renewal, and cancellation, to surface highest-leverage opportunities. Partner with product leadership to connect data insights with business context, working with Product, Engineering, and Design leaders to influence roadmap and prioritization decisions. Apply advanced methods including machine learning and causal inference to subscriptions-specific problems such as churn prediction, renewal optimization, and pricing or packaging experiments, adapting existing frameworks or developing new ones as needed. Design and run experiments using A/B/n and quasi-experimental approaches when testing is constrained to evaluate changes to member experience and quantify impact on member and business outcomes. Build member segmentation by analyzing member behavior in Subscriptions to support better targeting, personalization, and offer strategy. Contribute to an AI-native roadmap by identifying opportunities for AI/ML within the subscriptions experience, helping design measurement plans, and linking model performance to member and business outcomes. Mentor and support the team through experimentation rigor and best practices, and by contributing to hiring and calibration when needed. What you bring 7+ years of experience in data science and analytics, with a track record of driving measurable impact within a product area or initiative. Experience with subscription, membership, or lifecycle-based products is strongly preferred, and fintech experience is a plus. Analytical translation skills to turn ambiguous product questions into structured analyses and actionable recommendations. Experimentation and causal inference experience, including designing and interpreting experiments and applying causal inference when experimentation is constrained. Segmentation and experiment judgment with the ability to balance statistical rigor and business considerations. Lightweight machine learning capability, including building offline classification and regression models to inform business decisions. Experience building reusable assets such as analytical frameworks, methodologies, or tools used by others. Communication and influence skills, including working effectively with Director-level partners across business and technical teams. Execution in ambiguity, with the ability to make fast, data-driven decisions in a fast-paced environment. AI-native tools experience to plan, implement, and synthesize analyses across use cases such as experiment readouts and retention or churn deep dives. Education in BS or MS in Statistics, Mathematics, Operations Research, Computer Science, Engineering, Econometrics, or a related field. Role overview This role is the analytical partner to the Subscriptions product team, focused on using data to improve member experience from trial and conversion through renewal and retention. The position emphasizes scientific rigor, experimentation, and the application of machine learning and causal inference to drive subscription value. Location: Oakland, CA (onsite) #J-18808-Ljbffr DataJobs.com