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Senior Business Data Scientist

Category Data Location Mountain View, California Job ID 2024-67815
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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

We are seeking a highly motivated and experienced Senior Business Data Analyst 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!

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.
  • Cross-Functional Collaboration: Partner with product, digital and customer support teams to identify opportunities, create data-driven strategies, and influence decision-making.
  • Stay Current with Industry Trends: Keep up with evolving trends and advancements in data analytics to drive innovation and continuously improve business processes.

Qualifications

  • 4+ 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
  • Intermediate knowledge of designing experiments (A/B/n) and measuring their impact using descriptive and inferential statistical methods
  • Early understanding of Causal Inference methods (Propensity Score, DiD, Synthetic Control, etc..) and when to use them to answer key business questions
  • Knowledge of programming languages (e.g., Python, R) and building ML models (supervised and unsupervised)
  • Experience with AI/GenAI tools for automating tasks and building custom implementations is highly preferred
  • Strong data storytelling skills, with a proven ability to rapidly construct impactful visualization, communicate insights and influence leadership
  • Excellent communication and interpersonal skills, with the ability to collaborate effectively with technical and non-technical 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; Equivalent experience will be considered
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