Senior Data Scientist, SFS

Block is one company built from many blocks, all united by the same purpose of economic empowerment. The blocks that form our foundational teams — People, Finance, Counsel, Hardware, Information Security, Platform Infrastructure Engineering, and more — provide support and guidance at the corporate level. They work across business groups and around the globe, spanning time zones and disciplines to develop inclusive People policies, forecast finances, give legal counsel, safeguard systems, nurture new initiatives, and more. Every challenge creates possibilities, and we need different perspectives to see them all. Bring yours to Block.

The Role

As a Data Scientist with Square Financial Services, you will support the credit policies and machine learning models that power our banking and lending business. This includes established and fast-growing products like Square Loans that are widely used and beloved by our sellers and make a material contribution to Block's business.

This role sits within the team that owns the underwriting and ML models for these products, and the work will have an immediate impact on our credit and product strategy. By deeply analyzing our products and policies, designing and evaluating experiments, and partnering with ML engineers to support model development and evaluation, you will drive forward our ability to make credit available to more sellers in more contexts sustainably. We are looking for impact-driven "full stack" contributors that can develop a deep understanding of our products and engage across the spectrum from business strategy discussions to statistics and implementation details. You'll work closely with team members from a broad range of functions including ML, product, software engineering, operations, and capital markets.

You Will

• Analyze large datasets using SQL and Python to surface actionable insights that directly inform our product and credit strategy
• Approach problems from first principles, using a variety of statistical and mathematical modeling techniques to research and understand customer behavior and loan performance
• Design and analyze A/B experiments and employ pseudo-experimental techniques like causal inference and difference-in-difference
• Use SQL and Python to identify and curate new data sources for modeling, making sense of messy datasets and bringing clarity to business decisions
• Partner closely with ML engineers throughout the modeling lifecycle to develop, deploy, evaluate, and monitor models and credit policies
• Maintain and improve our systems for simulating the impacts of model/policy changes and the decision engine that implements those rules in production
• Effectively communicate your work with team leads and cross-functional stakeholders on a regular basis
• Build, visualize and report on metrics that drive strategy and facilitate decision making for key business initiatives

You Have

• Minimum of 8 years of related experience with a Bachelor's degree; or 6 years and a Master's degree; or a PhD with 3 years experience; or equivalent experience.
• A background in Statistics, Mathematics, Biostatistics, Economics or related quantitative field
• Advanced proficiency with SQL and Python for data analysis
• Experience designing and evaluating experiments at scale
• Ability to turn unstructured business problems into concrete analyses that yield actionable insights and recommendations
• Working understanding of core ML concepts, ideally with some experience evaluating or otherwise working with production models
• Experience defining and building product metrics in data visualization tools (e.g. Looker, Mode)
• Previous exposure to or interest in finance is helpful but not required

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 throughou