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Overview

How should Intuit be using causal inference methods to make decisions across marketing, product, and business strategy?

We’re building out a causal inference team, and we are looking for a Senior Staff Data Scientist that's ready to lead the way.

Being part of our cross-functional Decision Science Team means you'll be at the forefront of driving business performance. We empower our leaders, product managers, marketing managers, and analysts to make better decisions, uncover new opportunities, and shape strategy by tackling complex, high-stakes technical challenges using advanced quantitative methods, including experimental methods, causal inference, and machine learning.

As a tech lead for end-to-end causal inference projects at Small Business Solutions Group at Intuit, you'll be instrumental in shaping our most critical decisions. This unique opportunity allows you to join as a trailblazer and redefine the application of econometrics/statistics in a major tech company from the ground up.

Responsibilities

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

• At least 5 years of experience applying statistical and econometric 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.

• 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.

Qualifications

• Broad influence over the Decision Science Team’s agenda and roadmap that outlines how we can use causal inference to develop capabilities that deliver hundreds of millions of dollars of business value.

• Set the gold standard for causal inference at Intuit.

• Advise and mentor other economists and data scientists on scientific best-practices and on leveraging causal inference 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 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.

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits (https://www.intuit.com/careers/benefits/full-time-employees/) ). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:

Bay Area: $204,500-$276,500

Southern California: $197,500-$267,500

EOE AA M/F/Vet/Disability. Intuit will consider for employment qualified applicants with criminal histories in a manner consistent with requirements of local law.