Data Scientist, Payments

About the role

We are looking for a quantitative, AI‑fluent early‑career professional to fill a data science role focused on payments data across Square and Cash App. You will partner closely with Product, Operations, Finance, and Engineering, leveraging data tools to optimize our payments platform from success rate, to cost efficiency, to risk mitigation. In addition to vertical work focused on the Payments domain, we also expect you to contribute to horizontal initiatives across the broader Data Org from data systems, to process and tooling.

Responsibilities

• Leverage AI to create scalable data tools, agents, and automations
• Partner with Product, Engineering, Finance, and Operations teams to systemize and make data-driven decisions
• Measure and optimize the cost and performance of our payments stack
• Serve as a subject‑matter expert on our payments business and implementation
• Proactively identify gaps and opportunities in our processes
• Design, run, and analyze experiments
• Independently research questions and produce actionable insights
• Build ETL pipelines, dashboards, and machine learning models
• Translate open‑ended business needs into practical data solutions
• Design, implement, and maintain data systems and system architecture
• Stand up, maintain, and improve cloud data infrastructure and tooling
• Operationalize data processes and systems

Requirements

• A bachelor’s degree in a quantitative field with a strong academic record
• Experience working with code at an internship
• Experience working with large datasets using code
• Strong analytical expertise and business acumen
• Strong ability to communicate with non‑technical partners
• Knowledge of systems architecture and cloud infrastructure
• Bonus: experience with payments or banking

Skills

• SQL
• Python
• AI tools (to accelerate development, improve data workflows, and automate processes)
• Cloud infrastructure and tooling
• Data systems architecture
• Building ETL pipelines, dashboards, and machine learning models
• Designing, running, and analyzing experiments
• Translating open‑ended business needs into practical data solutions

Benefits

• Remote work
• Medical insurance
• Flexible time off
• Retirement savings plans
• Modern family planning

Pay

Block takes a market‑based approach to pay. U.S. locations are categorized into four zones based on a cost‑of‑labor index. The successful candidate’s starting pay will be determined by job‑related skills, experience, qualifications, work location, and market conditions. The current ranges are:

• Zone A: $111,700 USD – $167,500 USD
• Zone B: $106,100 USD – $159,100 USD
• Zone C: $100,500 USD – $150,700 USD
• Zone D: $95,000 USD – $142,400 USD