We are seeking a highly motivated and experienced Sr. Data Scientist to join our Customer Success Data Science team. In this role, you'll drive data-driven strategies to measure and optimize the performance of the Business Tax product, with a specific focus on expert-led customer experience initiatives - the moments when tax experts engage directly with customers to help them file their taxes, understand deductions, and navigate complex business tax scenarios. You'll be at the center of proving what works, what doesn't, and where we should invest next to grow the Business Tax business. If you're passionate about connecting customer experience investments to measurable business outcomes, we'd love to hear from you!

Responsibilities

p]:inline'> Measure Customer Experience Impact: Own the analytical narrative for how expert-touch initiatives (proactive outreach, in-product expert guidance, post-filing check-ins, and other advisory touchpoints) translate into filing behavior, product adoption, and long-term customer value.

p]:inline'> Strategic Recommendations: Provide actionable recommendations using diverse data sets and business knowledge, even when complete data is unavailable, to support strategic decisions on where and when to invest expert capacity.

p]:inline'> Define KPIs and Success Metrics: Establish the key indicators that tell us whether expert-customer engagements are driving Business Tax outcomes - filing completion, retention, deduction guidance uptake, and lifetime value - ensuring alignment with company objectives and clear measures of success.

p]:inline'> Data Visualizations: Translate complex data into clear, accessible visualizations that help product, expert operations, and leadership stakeholders understand key insights and make informed decisions.

p]:inline'> Experimentation and A/B Testing: Design, execute, and analyze A/B tests and other experiments using a hypothesis-driven approach - including tests of expert engagement timing, channel, and content. Provide insights and recommendations based on test outcomes to optimize business strategies.

p]:inline'> Predictive Analytics and Modeling: Develop predictive models and methodologies to identify which Business Tax customers benefit most from expert engagement, uncover growth opportunities, and support long-term business planning.

p]:inline'> Enable Self-Serve Analytics: Define and implement standardized metrics, reports, and dashboards for the Business Tax expert experience. Work with Data Engineering to ensure data quality and enhance real-time analytic capabilities across the customer-expert journey.

p]:inline'> AI/GenAI Integration: Collaborate with AI teams to integrate AI/GenAI solutions into the expert-customer workflow - measuring how AI-assisted expert tools change outcomes, effort, and customer satisfaction.

p]:inline'> Cross-Functional Collaboration: Partner with product, expert operations, marketing, and customer support teams to identify opportunities, create data-driven strategies, and influence decision-making on the Business Tax roadmap.

Qualifications

p]:inline'>4+ years of experience working with product analytics, customer care analytics, customer experience analytics, or other applied analytics roles - ideally with exposure to expert-assisted or high-touch service models

p]:inline'>Advanced proficiency in SQL, 'big data' technologies (e.g., Redshift, Spark, Hive, BigQuery, Databricks), and BI tools (e.g., Tableau, Qlik, Dash). Qlik certification is a big plus

p]:inline'>Deep expertise in experimentation design (A/B/n, bandits, painted-door) and causal inference (Propensity Score, DiD, Synthetic Control) - including comfort applying causal methods when clean experiments aren't feasible (e.g., measuring the impact of expert engagements that can't always be randomized)

p]:inline'>Understanding of AI-native architectures and GenAI platforms; able to assess implications for expert workflows, customer interactions, and measurement

p]:inline'>Strong business acumen and the ability to translate business strategy into testable hypotheses and a coherent learning agenda

p]:inline'>Strong data storytelling skills, with a proven ability to rapidly construct impactful visualization, communicate insights and influence leadership

p]:inline'>Excellent communication and interpersonal skills, with a proven ability to build trust and collaborate seamlessly across technical, business, and cross-functional teams

p]:inline'>Comfortable working in a fast-paced environment and have flexibility to shift priorities when needed

p]:inline'>Bachelor's degree in Engineering, Data Science, Statistics, Mathematics, Computer Science, Economics or related quantitative field; Master's Degree preferred

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 ). 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 $149,500 - $202,500