Intuit Inc.
Senior Staff Data Scientist
Intuit Inc. - Mountain View, California, us, 94039
Work at Intuit Inc.
Overview
- View job
Overview
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 help small and mid-market business customers manage their money. We collaborate with Product Management, Commercial, Finance, Business Operations, Design, and Engineering teams to foster data-driven decisions through strategic thinking, data analysis, experimentation, and predictive analytics.
As the founding Senior Staff Data Scientist working on a new product and a strategic initiative within the company, you will analyze data to uncover actionable insights and make recommendations that will fuel the growth of this new product. The ideal candidate will have a strong background in quantitative analysis using large data sets, demonstrated growth hacking experience, and expertise 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.
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.
Minimum Qualifications
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 a strong foundation in predictive modeling, customer segmentation, and experimentation.
Ability to formulate data-backed strategies that will drive significant business growth and increase customer benefits.
Ability to generate hypotheses grounded in customer behavior, industry trends, and external market factors. Experience in the fintech or SMB space is highly preferred.
Experience designing and interpreting complex experiments beyond traditional A/B testing methods.
Proven experience in building reusable and scalable analytics solutions, focusing on efficiency and avoiding duplication.
Outstanding communication skills, with the ability to influence decision-makers and build consensus across teams.
Quick learner, adaptable, capable of working independently or in a team within a fast-paced environment.
Experience applying statistics and machine learning techniques to solve complex business problems, such as propensity for feature adoption, customer health scoring, or next best action models.
Technical Skills:
Advanced SQL skills and proficiency with visualization tools like Qlik, Tableau, Plotly Dash.
Strong analytical and modeling skills using Python (e.g., numpy, pandas, scikit-learn).
Familiarity with Linux/OS X command line, version control software (git), and general software development practices.
Preferred Additional Qualifications:
Experience addressing growth-related challenges at financial technology companies serving consumers or SMBs.
Familiarity with Generative AI and other emerging technologies to accelerate insights from multi-modal data.
#J-18808-Ljbffr
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 help small and mid-market business customers manage their money. We collaborate with Product Management, Commercial, Finance, Business Operations, Design, and Engineering teams to foster data-driven decisions through strategic thinking, data analysis, experimentation, and predictive analytics.
As the founding Senior Staff Data Scientist working on a new product and a strategic initiative within the company, you will analyze data to uncover actionable insights and make recommendations that will fuel the growth of this new product. The ideal candidate will have a strong background in quantitative analysis using large data sets, demonstrated growth hacking experience, and expertise 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.
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.
Minimum Qualifications
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 a strong foundation in predictive modeling, customer segmentation, and experimentation.
Ability to formulate data-backed strategies that will drive significant business growth and increase customer benefits.
Ability to generate hypotheses grounded in customer behavior, industry trends, and external market factors. Experience in the fintech or SMB space is highly preferred.
Experience designing and interpreting complex experiments beyond traditional A/B testing methods.
Proven experience in building reusable and scalable analytics solutions, focusing on efficiency and avoiding duplication.
Outstanding communication skills, with the ability to influence decision-makers and build consensus across teams.
Quick learner, adaptable, capable of working independently or in a team within a fast-paced environment.
Experience applying statistics and machine learning techniques to solve complex business problems, such as propensity for feature adoption, customer health scoring, or next best action models.
Technical Skills:
Advanced SQL skills and proficiency with visualization tools like Qlik, Tableau, Plotly Dash.
Strong analytical and modeling skills using Python (e.g., numpy, pandas, scikit-learn).
Familiarity with Linux/OS X command line, version control software (git), and general software development practices.
Preferred Additional Qualifications:
Experience addressing growth-related challenges at financial technology companies serving consumers or SMBs.
Familiarity with Generative AI and other emerging technologies to accelerate insights from multi-modal data.
#J-18808-Ljbffr