Data Scientist, Payments

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 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.

You Will

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

You Have

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, including SQL and Python

Experience using AI tools to accelerate development, improve data workflows, and automate processes

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

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.

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.

Zone A:
$111,700 — $167,500 USD

Zone B:
$106,100 — $159,100 USD

Zone C:
$100,500 — $150,700 USD

Zone D:
$95,000 — $142,400 USD

Application Guidelines

Candidates may submit up to 9 active applications within a 60-day period. Reapp