Job Description

Square’s mission is economic empowerment, and our team supports this by using data to understand and empathize with our customers, thereby allowing us to build a remarkable product experience. As a member of the team, you will use engineering, analytics, and machine learning to empower data-driven decision-making in the full lifecycle of product development and bringing our products to market. With support from the Invoices Data Science Lead, you will lead experimentation & growth plans, develop solutions to personalize product experiences, provide insights to our sellers about their business, and drive strategic decisions with data. 

You will:

• Partner directly with the Invoices product team to make data-driven decisions across the organization by applying descriptive and predictive analytics where it will have a material impact
• Apply a diverse set of tactics such as statistics, quantitative reasoning, and machine learning to research and produce insights
• Coordinate and solve complex projects that extend beyond the traditional boundaries of product domains, analytics, and data science
• Communicate analysis and decisions to high-level partners and executives in verbal, visual, and written media
• Lead the data strategy of embedded product engineering, to help make well-informed architecture and design decisions that affect data at Square
• Develop resources to empower data access and self-service so your expertise can be leveraged where it is most impactful

Qualifications

You have:

• 4+ years of analytics and data science experience or equivalent
• Experience building relationships to influence product partners with data
• Experience leading cross-functional projects that depend on the contributions of others in multiple disciplines
• Experience applying both statistical and machine-learning techniques to solve practical product problems such as predicting churn, LTV, cross-selling, and clustering user archetypes
• Familiarity with data warehouse design and best practices
• Fluency with data, analytics, and visualization technologies (we use SQL, Looker, and Python)

Nice to have: 

• M.S or Ph.D. in a quantitative field (mathematics, statistics, or similar STEM field)
• Experience working on business and product initiatives focused on growth and retention
• Familiarity with Marketing analytics and experimentation