Intuit's QuickBooks Money team is developing innovative tools to help customers get paid faster and with confidence. The Money Data Science team is dedicated to creating tools and services that dramatically increase the ability of small-medium businesses (SMBs) to manage cash flow, aiming to deliver delightful customer experiences and drive business impact by developing insights, models, and strategic thought partnership.
Requirements
- 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
- 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
- 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
Responsibilities
- Conceptualize business problems or opportunities, formulate hypotheses and goals, dene 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 renew 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
- 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.
Other
- 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.
- Ability to formulate data-backed strategies that will drive step-function growth for the business as well as increase customer benefit
- Ability to generate hypotheses grounded in customer behavior, industry trends, and external market factors. Experience in the fintech or SMB space is highly preferred.
- 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
