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 the TurboTax Monetization Analytics team as a Senior AI Scientist! Intuit’s Consumer Group (CG) has an exciting opportunity for a best in class, data-driven leader with a passion for product analytics. As a Senior Data Scientist on the Monetization Analytics team, you will be in a highly influential position to inform product strategy and drive maximum business results through experimentation and advanced statistical methodologies.

Responsibilities

Perform hands-on data analysis and modeling to derive meaningful conclusions and solve complex problems. Extract insights and knowledge from structured and unstructured data using various techniques, including statistical analysis, machine learning, and data visualization in service to driving business decisions
Run regular A/B tests, gather data, perform statistical analysis, draw conclusions on the impact of product experiences and communicate results to peers and leaders to measure and optimize execution of data-driven strategies in the TurboTax Monetization space
Utilize models and develop advanced experimentation methods, such as synthetic controls, propensity score matching techniques etc. to establish causality and measure product performance
Manage data integration and engineering with Product platform for data hygiene
Provide guidance and support to business leaders and stakeholders on how best to harness available data in support of critical business needs and goals in standardization of reporting and strategy

Qualifications

5-7 years of experience working in web, product, marketing, or other related analytics fields, ideally with exposure to clickstream and experimentation.
Ability to tell stories with data, educate effectively, and instill confidence, motivating stakeholders to act on recommendations
Advanced proficiency in SQL, Tableau, and Excel, with expertise in modern advanced analytical tools and programming languages such as Python or R
Basic understanding of Causal Inference methods (Propensity Score, DiD, Synthetic Control, etc.) and when to use them to answer key business questions
Strong business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions
Experience in defining metrics and instrumenting data tracking in clickstream
Demonstrated ability of breaking down a business problem into analytical questions, developing sound hypotheses and finding evidence to prove or disprove them
Ability to manage multiple projects simultaneously to meet objectives and key deadline
A great storyteller and communicator and can build relationships with a diverse set of stakeholders, including both technical and non-technical colleagues
MS in Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent work experience is preferred