Manager 2, Data Science (Customer Success - Analytics)

Manager 2, Data Science (Customer Success - Analytics) Intuit - 4.1 Mountain View, CA Job Details 4 hours ago Qualifications Doctoral degree in statistics Data visualization software proficiency Machine learning/AI-based analysis Statistics Customer retention Computer Science Applied Mathematics Hypothesis testing Bachelor's degree in statistics Bachelor of Science R 8 years SQL Team development Bachelor's degree Ph.D. in statistics Doctor of Philosophy Team management Master of Science Mentoring Master's degree in statistics Experimental design Predictive analytics Master's degree in computer science A/B testing Data science Senior level AI Cross-functional collaboration Leadership Communication skills Python Database software proficiency Full Job Description Overview Company Overview Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With approximately 100 million customers worldwide using products such as TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible. Job Overview The Intuit Customer Success (ICS) Analytics Team is seeking an exceptional Data Science Senior Manager to drive innovation across two of Intuit's highest-priority growth areas: the Services business (Payments, Payroll, Bill Pay, and Lending) and the Mid-Market segment powered by Intuit Enterprise Suite (IES) — our AI-powered ERP platform purpose-built for complex, services-centric businesses. In this pivotal role, you will lead a high-performing data science team generating insights across both businesses — measuring and improving customer experiences in Payments, Payroll, and Lending (QuickBooks Capital) while powering a scalable, human-driven growth engine for IES. A defining aspect of this role is leveraging Intuit's AI + Human Intelligence (AI+HI) strategy — quantifying how the combination of AI and trusted human experts (ICs, CSMs, accounting domain experts) drives customer confidence, Services attach, and outcomes at scale — from human expert-led onboarding and CSM-driven customer health management. If you are passionate about data, skilled at building teams, and excited to shape Intuit's next chapter across Services and Mid-Market, we'd love to hear from you. Responsibilities Build, lead, and mentor a team of data scientists spanning Services (Payments, Payroll, Lending) and Mid-Market / IES Customer Success data science and analytics, ensuring growth in technical depth, business acumen, and leadership skills. Define and own the data strategy for the Services and Mid-Market segments — measuring funnel health, product adoption, and customer retention across QBO Advanced, IES, Human Capital Management and Money, and surfacing data-driven opportunities to improve conversion, attach, and consumption. Lead measurement and experimentation for expert programs, capturing the incremental value of human expertise in driving feature adoption, Services attach, and customer confidence. Partner with Customer Success teams to evolve the Customer Health Score (CHS) — including predictive churn models, feature adoption signals, and next-best-action recommendations — enabling CSMs and ICs to intervene proactively before customers disengage. Generate data-driven insights for partner-led growth motions, helping the business understand what drives partner confidence, client onboarding velocity, and long-term customer health. Translate complex business problems — across Services funnels, Desktop-to-IES migrations, multi-entity customer complexity, and segmented success models — into well-scoped analytical projects with clear metrics and measurable impact. Provide clear, actionable recommendations to senior leaders to influence Services and IES Customer Success strategy, GTM investment decisions, and segment-level priorities through rigorous, data-driven insights. Build and influence the metrics framework used to measure performance across both businesses, including Services attach and consumption, tNPS, Customer Health Score, Net Revenue Retention (NRR), and feature adoption. Provide technical leadership in applying advanced statistical, machine learning, and experimental design methods — including causal inference and A/B testing — to validate program hypotheses and optimize customer experiences. Champion a culture of data-driven innovation, driving continuous improvement in data science methodologies, tools, and practices across the ICS Analytics organization. Role-model "win-together" collaboration while challenging the status quo and driving change across teams regardless of organizational structure. Qualifications BS, MS, or PhD in Statistics, Computer Science, Applied Math, Econometrics, Operations Research, or related field. 8+ years of experience as a data scientist, analyst, or data-driven business leader, with a proven track record of delivering measurable business impact. Advanced skills in SQL, Python, R, and other analytical tools, with practical experience using data visualization platforms. Deep expertise in at least one core area: experimentation (A/B testing, causal inference), predictive modeling, machine learning, or statistical analysis. Strong collaboration and communication skills, with ability to influence business, marketing, product decisions. Proven ability to deliver end-to-end data science solutions that create customer or business value. Ability to balance strategic thinking with hands-on execution in ambiguous, high-growth environments. 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: