Senior Data Scientist, Risk

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 Machine Learning & Decision Science 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 through machine learning solutions or analysis.

The Risk Data Scientist will use analytical skills to identify and prevent the payment risks. You will lead experimentations to promote Risk effectiveness throughout Square. You will partner with product, engineering, operations, policies and sales to influence Squares global Risk road map and processes. You will have a chance to own the key metrics, develop data pipelines, ETL. You will also make direct impact to our key success metrics via building machine learning solutions, risk detection rule development and deployment.

You Will:

• Diagnose problems and develop compelling, data-driven recommendations
• Develop and maintain multiple data pipelines and ETLs
• Partner with Product, Engineering, and operation teams to design solutions to business problems, influence product roadmaps, and solution 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

• A BS/BA in Statistics, Mathematics, Operations Research, Engineering, Computer Science, Economics, or a related quantitative/technical field
• 7+ years of relevant experience (or masters and 4+ years)
• Experience with SQL, Python and Looker
• Experience with machine learning model development and deployment
• 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 risk, trust and safety, payments, or spam prevention

Additional Information

Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.

Zone A: USD $152,100 - USD $185,900
Zone B: USD $144,500 - USD $176,700
Zone C: USD $136,900 - USD $167,300
Zone D: USD $129,300 - USD $158,100

To find a location’s zone designation, please refer to this resource. If a location of interest is not listed, please speak with a recruiter for additional information. 

Full-time employee benefits include the following:

• Healthcare coverage (Medical, Vision and Dental insurance)
• Health Savings Account and Flexible Spending Account
• Retirement Plans including company match 
• Employee Stock Purchase Program
• Wellness programs, including access to mental health, 1:1 financial planners, and a monthly wellness allowance 
• Paid parental and caregiving leave
• Paid time off (including 12 paid holidays)
• Paid sick leave (1 hour per 26 hours worked (max 80 hours per calendar year to the extent