Intuit’s Global Business Solutions Group (GBSG) is dedicated to creating tools and services that dramatically increase the ability of small-medium businesses (SMBs) to manage cash flow. At the center of this mission, the QuickBooks Money team is developing innovative tools to help customers get paid faster and with confidence. Our expanding suite of offerings and new go-to-market strategies aim to further enhance SMBs' ability to accept payments seamlessly.

The Money Data Science team within the GBSG Data & Analytics organization aims to deliver delightful customer experiences and drive business impact by developing insights, models, and strategic partnerships that assist small and mid-market business customers in managing their money. We collaborate with Product Management, Commercial, Finance, Business Operations, Design, and Engineering teams to promote data-driven decision-making through strategic thinking, data analysis, experimentation, and predictive analytics.

As the founding Senior Staff Data Scientist working on a new product and strategic initiative within the company, you will analyze our data to uncover actionable insights and recommend strategies to fuel the growth of this new product. The ideal candidate will possess a strong background in quantitative analysis using large data sets, demonstrate growth hacking experience, and be proficient in data-driven decision-making.

Responsibilities

Conceptualize business problems or opportunities, formulate hypotheses and goals, define key metrics, and make actionable recommendations.

Drive strategic insights that shape the future of Money-movement ecosystem products within Intuit, impacting millions of small businesses.

Develop predictive models, conduct experiments beyond traditional A/B testing, and generate actionable customer insights to inform product innovation.

Build and apply durable customer segmentation patterns to refine product targeting, positioning, and customer experience.

Partner closely with Product Management, Marketing, Engineering, Design, and Analytics leaders to deliver insights that drive product strategy and growth.

Translate complex data insights into actionable recommendations for both technical and non-technical stakeholders and business leaders.

Intuit offers a competitive compensation package with a strong pay-for-performance rewards approach. The expected base pay range for this position in the Bay Area, California, is $204,500–$276,500. The role is eligible for a cash bonus, equity rewards, and benefits, in accordance with our plans and programs. Pay offered depends on factors such as knowledge, skills, experience, and location. We also prioritize ongoing pay equity, conducting regular comparisons across categories of ethnicity and gender.

The ideal candidate is a curious, proactive data scientist with experience in building scalable solutions, a strong understanding of customer behavior, and a passion for fintech.

BS or MS degree in Statistics, Mathematics, Operations Research, Computer Science, Econometrics, or related field.

10+ years of experience in data science or product analytics, preferably in fintech, with expertise in predictive modeling, customer segmentation, and experimentation.

Ability to formulate data-backed strategies to drive significant business growth and enhance customer benefits.

Experience in generating hypotheses based on customer behavior, industry trends, and market factors. Fintech or SMB experience is highly preferred.

Experience designing and interpreting complex experiments beyond traditional A/B testing.

Proven ability to build reusable, scalable analytics solutions focused on efficiency.

Outstanding communication skills to influence decision-makers and build consensus.

Quick learner, adaptable, and capable of working independently or in teams within a fast-paced environment.

Experience applying statistical and machine learning techniques to solve business problems, such as propensity modeling, customer health scoring, and next best action models.

Technical Skills:

Advanced SQL skills and proficiency in visualization tools like Qlik, Tableau, Plotly Dash.

Strong analytical and modeling skills using Python (libraries like numpy, pandas, scikit-learn).

Familiarity with Linux/OS X command line, version control (git), and software development practices.

Preferred Additional Qualifications:

Experience solving growth-related problems at financial technology companies serving consumers or SMBs.

Familiarity with Generative AI and other emerging technologies for multi-modal data insights.

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