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 Ecosystem 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 Staff Data Scientist on the Product Data Science team partnering with our Money Growth Mission 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, paying others, and managing cash flow. The ideal candidate will have a strong background in quantitative analysis using large data sets, demonstrated growth hacking experience, and in data-driven decision making.
ResponsibilitiesAs a Senior Staff 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 and GTM strategies 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 recommendationsDrive strategic insights that shape the future of Money-movement ecosystem products within Intuit, impacting millions of small businessesDevelop predictive models, conduct experimentation beyond A/B testing, and generate actionable customer insights that inform product innovationBuild and apply durable customer segmentation patterns to renew product targeting, positioning, and customer experiencePartner closely with Product Management, Marketing, Engineering, Design, and Analytics leaders to deliver insights that drive product strategy and growthTranslate complex data insights into actionable recommendations for technical and non-technical stakeholders, and business leadersThe 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 QualificationsBS or MS degree in Statistics, Mathematics, Operations Research, Computer Science, Econometrics or related field; equivalent experience will be considered10+ years of experience in data science or product analytics, preferably in fintech, with a strong foundation in predictive modeling, customer segmentation, and experimentationAbility to formulate data-backed strategies that will drive step-function growth for the business as well as increase customer benefitAbility 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 methodsDemonstrated experience in building reusable and scalable analytics solutions, with a focus on efficiency and avoiding duplication of workOutstanding communication skills with the ability to influence decision makers and build consensus with teamsQuick learner, adaptable, with the ability to work independently or as part of a team in a fast-paced environmentExperience 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 DashStrong 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 developmentPreferred Additional QualificationsExperience solving growth-related problems at financial technology companies serving consumer or SMBsFamiliarity with Generative AI and other evolving technologies to accelerate insights from multi-modal data
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