Staff Data Scientist, Experimentation

Key Skills

Java Programming, Analytical and Problem solving, Leadership, Design, Python Programming, Database, SQL, Big Data Technology, A/B Testing, R Programming, Algorithms, Data pipelines, Data Analysis

Job Description

At Intuit, we’re on a high priority mission to increase the value and velocity of all data-driven decisions impacting our products - TurboTax, Quickbooks, Mint, and Credit Karma. We are looking for a Data Scientist lead with deep expertise in experimentation, statistics, and prescriptive algorithms, solving complex big data problems and the ability to drive a cultural change. This role will partner closely with data leaders, analysts, and Engineering teams to drive company-level impact by identifying and implementing enhancements to our experimentation platform’s suite of services.

Qualifications

• Intellectual curiosity and a passion for experiment design, experiment methodology, and iterative learning
• Proficiency with relational database querying languages (e.g., SQL) and statistical analysis/programming languages (e.g., Python or R)
• A wide range of experience with experimentation (3+ years), including conducting and analyzing A/B tests with various applied statistical techniques (e.g., incrementality testing and causal inference)
• Experience making confident data-driven recommendations based on experiment results, and communicating these to stakeholders with various levels of technical knowledge
• Passionate about statistical methods and translating complex business problems into tractable statistical problems
• Ability to build durable data models with automated pipelines, dashboard templates and other solutions for analysts to leverage
• Entrepreneurial and self-directed, demonstrated ability to innovate and bias toward action in fast-paced environments
• Ability to tackle ambiguous and undefined problems

Responsibilities

• Contribute to the long-term technical vision and strategy, including the usage and implementation of different methods and metrics that will help stakeholders across the business evolve the way they leverage experimentation technology to drive impact
• Develop a detailed understanding of the Intuit’s experimentation platform, data architecture and measurement tools/services
• Continue to keep a pulse on broader industry best practices as well as challenges, ultimately enabling the ability to identify present and future opportunities and risks
• Identify and prioritize areas of opportunity, anticipate experimenter needs, and assess novel solutions
• Work with engineering and analysts to build and improve experimentation methods and metrics, ensuring high-quality output and impact
• Educate internal colleagues of various technical level on different experimentation methods, metrics, tools, and best practices