Intuit is looking to optimize customer support experiences and the end-to-end customer journey through data-driven strategies.
Requirements
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
Responsibilities
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.
Other
Partner with product, digital and customer support teams to identify opportunities, create data-driven strategies, and influence decision-making.
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.
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
