**Overview**

We are seeking a highly motivated and experienced Staff Data Scientist to join our Customer Success Analytics Team. In this role, you’ll drive data-driven strategies that optimize both human-assisted support experiences and the broader end-to-end customer journey. By partnering with cross-functional teams, you’ll deliver insights that enhance service design, improve operational efficiency, and elevate overall customer satisfaction. This is a unique opportunity to make a meaningful impact on both support experiences and strategic customer initiatives. If you’re passionate about shaping the future of customer success through data, we’d love to hear from you!

**What you'll bring**

● 8+ years of experience working with product analytics, web analytics, customer care analytics, or other customer experience analytics● Advanced proficiency in SQL, “big data” technologies (e.g., Redshift, Spark, Hive, BigQuery), and BI tools (e.g., Tableau, Qlik, Dash). Qlik certification is a big plus● Strong programming skills in Python or R; experience building ML and GenAI models, including automation and custom implementations● Deep expertise in experimentation design (A/B/n, bandits, painted-door) and causal inference (Propensity Score, DiD, Synthetic Control) with a strategic understanding of their application● Understanding of AI-native architectures and GenAI platforms; able to assess implications for data, testing, and behavior● Strong business acumen and the ability to translate business strategy into testable hypotheses and learning agendas● Strong data storytelling skills, with a proven ability to rapidly construct impactful visualization, communicate insights and influence leadership● Excellent communication and interpersonal skills, with a proven ability to build trust and collaborate seamlessly across technical, business, and cross-functional teams.● Comfortable working in a fast-paced environment and have flexibility to shift priorities when needed

● Bachelor’s degree in Engineering, Data Science, Statistics, Mathematics, Computer Science, Economics or related quantitative field; Master’s Degree preferred

**How you will lead**

● **Define KPIs and Success Metrics:** Establish key business indicators for projects, ensuring alignment with company objectives and clear measures of success.● **Strategic Recommendations:** Provide actionable recommendations using diverse data sets and business knowledge, even when complete data is unavailable, to support strategic decisions.● **Data Visualizations:** Translate complex data into clear, accessible visualizations that help stakeholders understand key insights and make informed decisions.● **Experimentation & A/B Testing:** Design, execute, and analyze A/B tests and other experiments using a hypothesis-driven approach. Provide insights and recommendations based on test outcomes to optimize business strategies.● **Predictive Analytics & Modeling:** Develop predictive models and methodologies to uncover growth opportunities and support long-term business planning.● **Enable Self-Serve Analytics:** Define and implement standardized metrics, reports, and dashboards. Work with Data Engineering to ensure data quality and enhance real-time analytic capabilities.● **AI/GenAI Integration:** Collaborate with AI teams to integrate AI/GenAI solutions into business processes, enhancing efficiency and innovation.● **Cross-Functional Collaboration:** Partner with product, digital and customer support teams to identify opportunities, create data-driven strategies, and influence decision-making.● **Leadership & Ownership:** Demonstrates boundaryless leadership and extreme accountability - proactively drives outcomes across teams and leads with influence, not authority.

● **Stay Current with Industry Trends:** Keep up with evolving trends and advancements in data analytics to drive innovation and continuously improve business processes.

EOE AA M/F/Vet/Disability. Intuit will consider for employment qualified applicants with criminal histories in a manner consistent with requirements of local law.