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Staff, Customer Marketing Segment Strategy Leader Defector
Job Description
•Overview•Intuit's TurboTax business serves millions of DIY customers every season — but a meaningful share of that base is at risk of defecting to Assisted competitors each year. This role owns the strategy and execution to stop that leakage: identifying which customers are most likely to defect, understanding why, and converting them into TurboTax Assisted offerings before they leave You'll sit at the center of a high-visibility, cross-functional mission team with a clear mandate and the runway to drive it. This is a rare opportunity to own a strategic growth lever end-to-end — from segmentation and modeling through outbound execution and exec-level reporting — with direct accountability for one of TurboTax's most important retention and conversion opportunities. •Responsibilities•_Cross-Functional Program Leadership_ + Own program management for the cross-functional Defector Mission Team, driving operating cadence, milestone accountability, and executive-level reporting across Data Science, Lifecycle/CRM, Outbound Sales, Product, and Finance. + Serve as the connective tissue across teams, ensuring strategy, modeling, and execution stay tightly aligned toward the save-rate target. _Segment Strategy & Acquisition Playbooks_ + Collaborate with Research and Data Science teams to define customer cohorts by defection driver (FUD, experience, price-value) and prioritize the highest-propensity segments for action. + Build acquisition playbooks tailored to each segment, and lead scoring and segmentation aligned to various data modeling frameworks + Partner with Marketing to ensure the top of the funnel is fueled with the right leads to support segment strategy _Data-Driven Targeting & Funnel Optimization_ + Partner with Data Science to operationalize the daily defector propensity model, translating scores into actionable outreach lists and test-and-learn campaigns. + Develop targeting strategy to filter out low-intent and self-serve leads before they reach Sales, and lead MQL → SQL conversion modeling and funnel analysis. _Pipeline & Capacity Planning_ + Manage pre-booking and appointment pipeline strategy for TY26 and year round engagement + Lead outbound lead pool sizing and capacity planning to support Concierge expansion. _Performance Measurement & Executive Reporting_ + Track and report against north-star metrics, both with cross functional stakeholders and senior leadership + Communicate progress and recommendations clearly to senior leaders and executives •Qualifications•+ Background in strategy, growth marketing or customer lifecycle management. + Comfortable operating at the intersection of data science and go-to-market execution — able to translate models and scores into real campaigns and outreach. + Strong program management skills, with a track record of driving cross-functional teams toward a shared, numeric outcome. + Self-starter who can lead and influence without direct authority across Data Science, Sales, Product, and Finance partners. Footer 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 (https://www.intuit.com/careers/benefits/full-time-employees/) ). 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: San Diego $164,000 - $222,000 Mountain View, CA $169,000- $229,000EOE AA M/F/Vet/Disability. Intuit will consider for employment qualified applicants with criminal histories in a manner consistent with requirements of local law.
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What they do
A Data Science Manager manages a team of data scientists, machine learning engineers and big data specialists. They lead data mining and collection procedures, ensure data quality and integrity, build analytic systems and predictive models, and test the performance of data science products.
$180,727 / year median in California
+17% projected growth