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
We are looking for a Data Scientist to join our Risk Data team. You'll build processes to root out high-risk activity across the Square platform of products. You will also manage top level Risk KPIs, establish core operational metrics, and make improvements by using machine learning solutions or through analysis.
The Risk Data Scientist will use analytical skills to identify and prevent fraud & credit risks. You will lead experimentations to promote Risk effectiveness throughout Square. You will partner with product, engineering, operations, machine learning engineers, policy and sales team to influence Square's global Risk road map and processes. You will own the key metrics, develop data pipelines, ETL. You will also make a direct impact on Square's priorities and Banking initiatives (primarily SQ's debit card) by building risk detection strategies, developing & tracking key success metrics, influencing partners through data and enabling growth of the business.
You Will

• Diagnose problems and develop compelling, data-driven recommendations
• Develop and maintain multiple data pipelines and ETLs
• Partner with Product, Engineering, Machine Learning Engineering, Policy and Operation teams to design solutions to business problems, influence product roadmaps, and develop new products/processes
• Have a chance to use machine learning tools to develop data-driven solutions.
• Promote creative risk solutions through third-party evaluation and integration with a focus on improving the seller experience
• Develop executive presentations for Squares leadership

Qualifications
BS/BA in Statistics, Mathematics, Operations Research, Management Science, Computer Science, or a related technical field, OR BS/BA in Criminal Justice, Economics, Business, or a related business field

• 5+ years of relevant experience (or masters degree with 3+ years of experience)
• Experience with SQL, Python and Looker
• Experience driving data-driven solutions and project-managing their implementation
• Experience answering unstructured questions and managing projects and tasks to a conclusion
• A passion for Square's mission
• Experience in risk, trust and safety, payments, or spam prevention

Qualifications
BS/BA in Statistics, Mathematics, Operations Research, Management Science, Computer Science, or a related technical field, OR BS/BA in Criminal Justice, Economics, Business, or a related business field

• 5+ years of relevant experience (or masters degree with 3+ years of experience)
• Experience with SQL, Python and Looker
• Experience driving data-driven solutions and project-managing their implementation
• Experience answering unstructured questions and managing projects and tasks to a conclusion
• A passion for Square's mission
• Experience in risk, trust and safety, payments, or spam prevention