Staff Business Data Analyst
Intuit
Staff Business Data Analyst
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
Come join Intuit as a Staff Business Data Analyst on the Finance Data Science and Strategy team. We are looking for creative problem solvers with a passion for delivering data-driven insights. This position works alongside finance, strategy, product management, marketing, and data engineering to deliver business results using data for insights and optimization.
Responsibilities
- Explore and educate stakeholders on new business growth opportunities, unit economics, product migration, cross-selling, product growth levers, price/spend optimization, etc.
- Perform end-to-end analytics using advanced SQL to extract business value and insights
- Leverage product and revenue data to inform decisions while clearly articulating key assumptions
- Disseminate business insights to cross-functional stakeholders and influence decision-making
- Define key metrics and educate partners on how to use them to view the business
- Develop and automate advanced analyses and calculations on LTV and CAC
Qualifications
- 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
Preferred Additional Experience:
- 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
- Excitement for small businesses and helping to solve the challenges they face