Overview

Come join Intuit as a Senior Data Scientist on the Finance Data Science & 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.

What you'll bring

• 4+ years relevant experience with a proven track record of leveraging analytics to drive significant business impact.
• Bachelor’s degree in a quantitative field - Business, Statistics, Engineering, Computer Science; Master’s preferred, or equivalent experience.
• 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.
• 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.
• Proficiency in visualization tools such as Tableau.

How you will lead

• 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.