Staff Business Data Analyst

Come join the Intuit Finance Data Science & Strategy team as a Staff Business Data Analyst! In this role, you will help drive data-backed strategic initiatives across the Intuit portfolio, primarily focused on opportunities within our Consumer Group. We are looking for creative problem solvers with a passion for delivering data-driven insights. You will partner closely with finance strategy, FP&A, data engineering, and various business partners to directly impact our business results and accelerate Intuit’s growth.

• Explore new opportunities to grow the business through analyses spanning unit economics, market dynamics, product migration, cross-selling, product growth levers, price/spend optimization, etc.
• Perform end-to-end analytics using advanced SQL to extract business insights that drive tangible value for our customers and result in business growth.
• Leverage data visualization and dashboarding tools such as Tableau to help uncover key business insights and improve team automation and self-service analytics.
• Leverage product and revenue data to inform decisions while clearly articulating key assumptions.
• Disseminate business insights to cross-functional stakeholders and influence decision-making.

• 6+ years relevant experience with a proven track record of leveraging analytics to drive significant business impact.
• Advanced SQL skills to get the data you need from a data warehouse (e.g., Redshift, Hive, SparkSQL, Athena) and perform data segmentation and aggregation from scratch.
• Understanding of statistics with regards to experimentation and regression.
• Passion for uncovering strategic opportunities and solving business problems.
• Proficiency in visualization tools such as Tableau or Qlik Sense.
• Excellent presentation and data storytelling. Demonstrated ability to explain complex technical issues to both technical and non-technical audiences.
• Experience with modern advanced analytical tools and programming languages such as Python, R, or some other scripting language.
• Working knowledge of Consumer Finance platforms’ (e.g., TurboTax) data and business model.
• High-level understanding of advanced statistical modeling techniques such as clustering, classification, regression, decision trees, random forest. Building such models is not a focus of this particular role. Comfort with these tools and concepts will be useful to solve particular problems or evaluate the performance of pre-built models.
• Understanding forecasting processes, financial reporting, time value of money, and other financial concepts.