
Staff Data Scientist - Product Growh
MOUNTAIN VIEW, CAJob$194–263K/yrSeen 4 days agoSeen in employer's feed 4 days ago
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At a glance
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Job overview
The Staff Data Scientist will partner with peers and leaders on the Product Growth team to identify and refine growth strategies. The role applies causal inference and advanced analytics to surface insights and develop hypotheses that support customer and revenue growth. It also contributes to product funnel optimization, experimentation, cross-functional product enhancements, and improvements to instrumentation and data quality.
Skills & qualifications
Skills
Qualifications
Full job description
Overview
The Global Business Solutions Group (GBSG) Product Growth team is dedicated to accelerating business outcomes through a data-driven, product-led approach to growth. We leverage Product-Led Growth (PLG) tactics, scalable growth loops, and rigorous experimentation to uncover and amplify the highest-impact opportunities across the product ecosystem.
Our team unites exceptional talent across disciplines to execute rapid tests, conduct deep analytics, and foster cross-functional collaboration that drives both customer value and business performance.
As a Staff Data Scientist, you will operate as a senior individual contributor, partnering closely with peers and leaders to identify, validate, and refine innovative growth strategies. Your expertise—especially in causal inference and advanced analytics—will be instrumental in surfacing critical insights and translating them into actionable hypotheses that fuel sustained customer and revenue growth.
Responsibilities
Set Technical Vision and Strategy:
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Contribute to and help refine a data science roadmap aimed at driving product funnel optimization and scalable growth initiatives.
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Apply rigorous causal inference methods, advanced statistical modeling, and machine learning techniques to turn complex data into actionable insights.
Drive Deep Analytics & Experimentation:
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Develop an integrated view of the customer journey across various business metrics, quickly familiarizing yourself with new areas to pinpoint growth opportunities.
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Design, implement, and analyze targeted experiments to validate hypotheses, ensuring each initiative is built on data-driven insights and sound causal analysis.
Collaborate Across Functions:
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Work closely with Product, Engineering, Design, and other cross-functional teams to translate data insights into strategic product enhancements.
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Support ongoing improvements in instrumentation, data quality, and logging practices to enrich our analytical capabilities and understanding of customer behavior.
Lead by Example:
- Serve as a technical SME within the Product Growth team, championing analytical rigor and innovative problem-solving approaches.
Operate with Agility and Impact:
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Rapidly assimilate diverse business metrics and data sources to uncover insights and propose high-impact hypotheses.
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Balance rigorous technical analysis with swift, iterative execution to ensure that insights are quickly transformed into effective strategies.
Qualifications
Experience & Expertise:
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5+ years of experience in data science or analytics, with a proven record of applying advanced analytical methods to drive product and business growth.
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Demonstrated proficiency in causal inference techniques, statistical modeling, machine learning, and experimental design.
Technical Proficiency:
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Advanced skills in SQL, Python, R, and other analytical tools, with practical experience using data visualization platforms (e.g., Tableau, Power BI) to communicate insights.
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Experience with data integration and pipeline development is a plus.
Cross-Functional Collaboration & Leadership:
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Strong ability to quickly understand new business areas, mastering the essential data and metrics needed for informed decision-making.
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Excellent communication and storytelling skills, with a track record of effectively influencing both technical and non-technical stakeholders through data-driven insights.
Mindset & Attributes:
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A relentless focus on customer centricity, with deep empathy and a commitment to uncovering opportunities that improve customer experiences.
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An agile, entrepreneurial mindset, capable of balancing long-term strategic initiatives with rapid, iterative experimentation.
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may 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:
Mountain View $194,000 - $262,500
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.
How this job compares
Set against the 2,063 open Data Science jobs on Olive Jobs, counted November 4, 2026.
- Pay
- This posting$194–263K/yr
- California median$181–266K/yr240 salary ranges
- US median$135–236K/yr1,479 salary ranges
This range's midpoint, $228K, is close to the California median midpoint ($223K) — in the middle half of Data Science salary ranges in California.
- Openings
- Olive Jobs lists 309 open Data Science jobs in California and 2,063 across the US. 5% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 5 years of experience; Data Science postings that state a minimum ask for 6 years at the median (1,665 postings).
- Education
- 921 of the 2,063 open Data Science jobs (45%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 4, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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