Intuit
Senior Staff Data Scientist
How should Intuit be using causal inference methods to make decisions across marketing, product, and business strategy? We’re building a causal inference team and are looking for a Senior Staff Data Scientist ready to lead the way. As part of our cross‑functional Decision Science Team, you will drive business performance, empower leaders and analysts, and tackle high‑stakes technical challenges using advanced quantitative methods such as experimental design, causal inference, and machine learning.
Responsibilities
A bachelor’s degree in Statistics, Economics, or a related quantitative field is required. Advanced degrees, particularly a master’s or PhD, are highly desirable.
At least 5 years of experience applying statistical and econometric skills to decision‑making.
Demonstrated expertise in causal inference—including synthetic controls, regression discontinuity, instrumental variables, and other rigorous methods.
Strong track record of applying cutting‑edge econometric methods within a fast‑paced, dynamic environment.
Ability to navigate 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 for using causal inference to generate business value.
Set the gold standard for causal inference at Intuit.
Advise and mentor other economists and data scientists on scientific best practices and how to deliver business value.
Identify quasi‑experimental opportunities, conduct relevant analyses, communicate results to leadership, and collaborate to translate findings into action.
Establish processes and systems to create scalable capabilities rather than one‑off analyses.
Anticipate future business challenges and design 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 convey uncertainty.
Intuit provides a competitive compensation package with a strong pay‑for‑performance rewards approach. This position is eligible for a cash bonus, equity rewards, and benefits. Pay is based on job‑related knowledge, skills, experience, and work location. To drive fair pay, Intuit conducts regular comparisons across ethnicity and gender. Expected base pay ranges: Bay Area: $204,500–$276,500 Southern California: $197,500–$267,500
Seniority level: Mid‑Senior level Employment type: Full‑time Job function: Engineering and Information Technology Industry: Software Development
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Responsibilities
A bachelor’s degree in Statistics, Economics, or a related quantitative field is required. Advanced degrees, particularly a master’s or PhD, are highly desirable.
At least 5 years of experience applying statistical and econometric skills to decision‑making.
Demonstrated expertise in causal inference—including synthetic controls, regression discontinuity, instrumental variables, and other rigorous methods.
Strong track record of applying cutting‑edge econometric methods within a fast‑paced, dynamic environment.
Ability to navigate 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 for using causal inference to generate business value.
Set the gold standard for causal inference at Intuit.
Advise and mentor other economists and data scientists on scientific best practices and how to deliver business value.
Identify quasi‑experimental opportunities, conduct relevant analyses, communicate results to leadership, and collaborate to translate findings into action.
Establish processes and systems to create scalable capabilities rather than one‑off analyses.
Anticipate future business challenges and design 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 convey uncertainty.
Intuit provides a competitive compensation package with a strong pay‑for‑performance rewards approach. This position is eligible for a cash bonus, equity rewards, and benefits. Pay is based on job‑related knowledge, skills, experience, and work location. To drive fair pay, Intuit conducts regular comparisons across ethnicity and gender. Expected base pay ranges: Bay Area: $204,500–$276,500 Southern California: $197,500–$267,500
Seniority level: Mid‑Senior level Employment type: Full‑time Job function: Engineering and Information Technology Industry: Software Development
Referrals increase your chances of interviewing at Intuit by 2×.
We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr