Staff Data Scientist, Square Banking

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, 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.

The Role

We are looking for experienced Data scientists to join Square's growing Banking organization. Square Loans has revolutionized the way businesses obtain the funding needed to achieve their goals. Unlike traditional business financing products, Square Loans are extended to pre-qualified sellers. If approved after a short application, sellers receive their funds as soon as the next business day, and repayment happens as a fixed percentage of daily card sales. As Square Loans expands its product features to help sellers meet their varying financing needs, you will leverage data solutions to shape and execute strategies that expand credit eligibility, enhance loan gross profit, and improve cohesive user experience with Square Banking products.

You Will

• Establish subject-matter expertise in Loans architecture from underwriting policy to loan loss recovery strategy and lead decision making and drive alignments across multiple job functions.
• Influence product roadmap and guide Square Loans team to navigate through product opportunities and problem ambiguities.
• Collaborate with Product, Engineers, Credit Policy, and Operations teams to launch experimental loan products and find opportunities to improve loan origination, loss recovery and compliance risk mitigation.
• Define goal metrics for measuring lending products success and set benchmarks for product optimization.
• Expand your influence in Block Data Science community by developing and evangelizing data solutions to improve analytics insightfulness and actionability.

You Have

• 8 years of data science, credit risk analytics, underwriting or related fields.
• Wide-ranging experience working on ambiguous problems of high business impact and resolving complex issues in innovative and efficient ways.
• Expertise in product growth, understanding and tracking user behavior using analytical lenses like engagement, conversion, cohorts, segmentation and funnel analysis.
• Efficiently prioritizes concurrent projects and can deliver quickly during critical moments especially for product launch, without compromising quality.
• Ability to build strong relationships with cross-functional stakeholders, clearly communicating findings and influencing product designs.
• Advanced proficiency with data, analytics, and visualization technologies (we use SQL, Looker, and Python).

Even better:

• Experience in business lending, business credit card, credit risk, underwriting is a huge plus.

We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances.We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible.