> Markdown version of [/jobs/ext/4199682-staff-data-scientist-product-growh](https://www.wearedevelopers.com/jobs/ext/4199682-staff-data-scientist-product-growh). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Data Scientist - Product Growh - **Company:** Intuit Inc. - **Location:** San Diego, CA, United States - **Experience:** Expert - **Salary:** $194,000 - $262,500 - **Contract:** Permanent contract - **Skills:** Business Analytics Applications, Data Analysis, Data Integration, R (Programming Language), Python (Programming Language), Machine Learning, Power BI, SQL Databases, Tableau (Software), Data Logging, Data Pipelines - **Published:** October 31, 2026 - **Apply:** https://dejobs.org/x/x/A087BF97D5584B028C27264DA3002DB3/job/ ## About the Role Experience & Expertise: * 5+ years of experience in data science or analytics, with a proven record of applying advanced analytical methods to drive product and business growth. * Demonstrated proficiency in causal inference techniques, statistical modeling, machine learning, and experimental design. Technical Proficiency: * 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. * Experience with data integration and pipeline development is a plus. Cross-Functional Collaboration & Leadership: * Strong ability to quickly understand new business areas, mastering the essential data and metrics needed for informed decision-making. * Excellent communication and storytelling skills, with a track record of effectively influencing both technical and non-technical stakeholders through data-driven insights. Mindset & Attributes: * A relentless focus on customer centricity, with deep empathy and a commitment to uncovering opportunities that improve customer experiences. * An agile, entrepreneurial mindset, capable of balancing long-term strategic initiatives with rapid, iterative experimentation. ## Description 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: * Contribute to and help refine a data science roadmap aimed at driving product funnel optimization and scalable growth initiatives. * Apply rigorous causal inference methods, advanced statistical modeling, and machine learning techniques to turn complex data into actionable insights. Drive Deep Analytics & Experimentation: * Develop an integrated view of the customer journey across various business metrics, quickly familiarizing yourself with new areas to pinpoint growth opportunities. * 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: * Work closely with Product, Engineering, Design, and other cross-functional teams to translate data insights into strategic product enhancements. * 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: * Rapidly assimilate diverse business metrics and data sources to uncover insights and propose high-impact hypotheses. * Balance rigorous technical analysis with swift, iterative execution to ensure that insights are quickly transformed into effective strategies.