Company Description
Since we opened our doors in 2009, the world of commerce has evolved immensely, and so has Square. After enabling anyone to take payments and never miss a sale, we saw sellers stymied by disparate, outmoded products and tools that wouldn't work together.
So we expanded into software and started building integrated, omnichannel solutions - to help sellers sell online, manage inventory, offer buy now, pay later functionality through Afterpay, book appointments, engage loyal buyers, and hire and pay staff. Across it all, we've embedded financial services tools at the point of sale, so merchants can access a business loan and manage their cash flow in one place. Afterpay furthers our goal to provide omnichannel tools that unlock meaningful value and growth, enabling sellers to capture the next generation shopper, increase order sizes, and compete at a larger scale.
Today, we are a partner to sellers of all sizes - large, enterprise-scale businesses with complex operations, sellers just starting, as well as merchants who began selling with Square and have grown larger over time. As our sellers grow, so do our solutions. There is a massive opportunity in front of us. We're building a significant, meaningful, and lasting business, and we are helping sellers worldwide do the same.
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 experience. The Food & Beverage team within Square is charged with empowering businesses of all kinds to start, run, and grow their businesses through advanced workflows, specialized products, business insights, and inclusion in the greater Square ecosystem. We are working on some of the highest priority focus areas for the company. This team owns multiple products that serve Food & Beverage sellers, such as the Point-of-Sale, the Kitchen Display, as well as the overall Square product experience in the Food & Beverage space.
As a Data Scientist, you will use data engineering, business intelligence, analytics, statistics, and machine learning to empower data-driven decision-making in the full lifecycle of product development and ensure a cohesive customer experience. You will lead efforts to define metrics that track progress against organizational goals, provide insights to our sellers about their business, and collaborate with a wide range of cross-functional partners to ensure we can drive strategic decisions for our Food & Beverage sellers with data.
You will:

• Partner directly with the Food & Beverage product team to make data-driven decisions by applying descriptive and predictive analytics where it will have a material impact
• Build foundational metrics and KPIs in business intelligence tools (e.g. Looker, Amplitude) to measure the health of our business
• Work with the engineering team to implement high quality product event logs
• Apply a diverse set of tactics such as statistics, quantitative reasoning, and machine learning to research and produce insights
• Prioritize rigorously amidst different stakeholders, ensuring your contributions have the most impact on Square's strategic decisions & bottom line
• Communicate analysis and decisions to high-level partners and executives in verbal, visual, and written media
• Develop resources to empower data access and self-service so your expertise can be leveraged where it is most impactful

Qualifications
You have:

• 5+ years of analytics and data science experience or equivalent
• Experience building relationships to influence product partners with data
• Experience leading and participating in cross-functional projects that depend on the contributions of multiple disciplines
• Experience applying both statistical and machine-learning techniques to solve practical product problems such as predicting churn and defining frameworks to measure success
• Fluency with SQL and Python, and experience with 1+ visualization technologies (we use Looker and Amplitude)

Qualifications
You have:

• 5+ years of analytics and data science experience or equivalent
• Experience building relationships to influence product partners with data
• Experience leading and participating in cross-functional projects that depend on the contributions of multiple disciplines
• Experience applying both statistical and machine-learning techniques to solve practical product problems such as predicting churn and defining frameworks to measure success
• Fluency with SQL and Python, and experience with 1+ visualization technologies (we use Looker and Amplitude)