Staff Data Scientist, Causal Inference

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.

Qualifications

A bachelor's degree in Statistics, Economics, Computer Science or a related quantitative field is required. Advanced degrees, particularly a Master's or PhD in economics or statistics, are highly desirable;

equivalent experience will be considered.

• At least 5 years of experience applying statistical / econometric and modeling skills in decision making.
• Demonstrated expertise in causal inference including but not limited to synthetic controls, regression discontinuity, and instrumental variables with a track record of rigorously solving problems with these methods.
• Applied experience leveraging machine learning including but not limited to predictive forecasting, explainable ML, and end-to-end model pipeline development to drive meaningful business impact
• Strong track record of applying cutting-edge econometric methods within a fast-paced, dynamic environment.
• A demonstrated ability to navigate through ambiguity and deliver results that significantly impact the business.
• Excellent communication skills and the ability to work effectively with both technical and non-technical colleagues.
• Proficiency in SQL and a statistical programming language such as Python and / or R.

Responsibilities

• Broad influence over the Decision Science Team’s agenda and roadmap that outlines how we can use causal inference and machine learning to develop capabilities that deliver hundreds of millions of dollars of business value.
• Set the gold standard for causal inference and predictive analytics at Intuit.
• Advise and mentor other economists and data scientists on scientific best-practices and on leveraging causal inference and machine learning to deliver business value.
• Identify quasi-experimental opportunities, conduct relevant analyses, communicate results to leadership, and collaborate with leadership to turn findings into actions.
• Establish processes and systems to create scalable capabilities and robust data products rather than one-off analyses.
• Anticipate future business challenges and key questions, designing methodologies, models, and solutions to address them.
• Use state-of-the-art time series and forecasting techniques to integrate micro and aggregate data, developing reliable forecasting models that adequately convey uncertainty.
• Engineer robust machine learning pipelines that can reliably power key business processes and customer-facing applications

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. The expected base pay range for this position is Bay Area California $180,500 - 244,000, Southern California $178,000 - 240,500.

This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs .

Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing pay equity for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.