Job Overview

Intuit’s Global Business Solutions Group (GBSG) is dedicated to creating tools and services that dramatically increases 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 Payments Product Data Science team on the GBSG Data & Analytics organization’s mission is to deliver delightful customer experiences and drive business impact by developing insights, models, and strategic thought partnership that helps small and mid-market business customers get paid and accelerates GBSG’s growth. We partner 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 a Senior Data Scientist on the Product Data Science team, you will dive deep into our data to uncover actionable insights and make recommendations that will influence the company’s strategic decisions, especially with building products that solve small & mid-market business customers’ biggest pain point of getting paid . The ideal candidate will have a strong background in quantitative analysis using large data sets, and in data-driven decision making.

Responsibilities

As a Senior Data Scientist on the Product Data Science team, you will dive deep into our data to uncover actionable insights and shape strategic decisions. Your contributions will directly impact our product development to address one of SMBs’ biggest challenges: getting paid on time. This role requires a strong background in quantitative analysis, data-driven decision-making, and expertise in working with large data sets

• 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 experimentation beyond A/B testing, and generate actionable customer insights that 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 technical and non-technical stakeholders, and business leaders

Qualifications

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
• 4+ 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 generate hypotheses grounded in customer behavior, industry trends, and external market factors. Experience in the fintech or SMB space is highly preferred.
• Experience in designing and interpreting complex experiments beyond traditional A/B testing methods
• Demonstrated experience in building reusable and scalable analytics solutions, with a focus on efficiency and avoiding duplication of work
• Outstanding communication skills with the ability to influence decision makers and build consensus with teams
• Quick learner, adaptable, with the ability to work independently or as part of a team in a fast-paced environment
• Experience using statistics and machine learning techniques to solve complex business problems within go-to-market and marketing areas, e.g., propensity for feature adoption, customer health scoring to identify customers at risk to cancel, next best action models etc. 

Technical Skills:

○ Advanced SQL skills and proficiency in visualization tools such as Qlik, Tableau, Plotly Dash

○ Strong analytical and modeling skills using Python (for its rich suite of statistical and modeling libraries like numpy, pandas, scikit-learn, etc.)

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

Preferred Additional Qualifications

• Experience solving growth-related problems at financial technology companies serving consumer or SMBs
• Familiarity with Generative AI and other evolving technologies to accelerate insights from multi-modal data