Intuit is seeking a Senior Data Scientist to drive data-driven strategies that enhance customer engagement, retention, and loyalty across all stages of the lifecycle, by applying advanced analytics to improve customer experiences and identify growth opportunities.
Requirements
- Advanced proficiency in SQL, “big data” technologies (e.g., BigQuery, Redshift), and BI tools (e.g., Tableau, Dash), and familiarity with vendor platforms a plus (e.g., Google Analytics GA4, Segment, Amplitude)
- Strong programming skills in Python; experience building ML models (GenAI models a plus), including automation and custom implementations
- Deep expertise in experimentation design (A/B/n) 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.
Responsibilities
- Experimentation and 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 and 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
- AI/GenAI Integration: Collaborate with AI teams to integrate AI/GenAI solutions into business processes, enhancing efficiency and innovation.
- 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.
Other
- 4+ years of experience working in web data science or product data science
- Leadership and 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.
- Cross-Functional Collaboration: Partner with product and sales teams to identify opportunities, create data-driven strategies, and influence decision-making.
- Comfortable working in a fast-paced environment and have flexibility to shift priorities when needed
