Senior Data Scientist

Intuit | San Diego, CA

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Posted Date 12/19/2024
Description

Come join the TurboTax Monetization Analytics team as a Senior Data 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
  • 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

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