Data Scientist, Payments

Block (Square)
San Francisco, CA
On-site

Who this role is best for

Strong fit for early-career professionals with AI fluency and data engineering skills who thrive in collaborative, payments-focused environments.

Best fit for

  • Early-career professionals with AI fluency and data engineering skills who enjoy cross-functional collaboration
    — “We are looking for a quantitative, AI-fluent early-career professional”
  • Candidates with hands-on experience in building ETL pipelines and machine learning models for payments systems
    — “Build ETL pipelines, dashboards, and machine learning models”
  • Individuals who can translate business needs into technical data solutions with a focus on payments and financial services
    — “Translate open-ended business needs into practical data solutions”

Things to consider

  • The role requires a strong grasp of cloud infrastructure and system architecture, which may demand additional technical preparation
    — “Knowledge of systems architecture and cloud infrastructure”

How to stand out

  • Highlight experience with AI tools in automating data workflows and improving efficiency
    — “Experience using AI tools to accelerate development, improve data workflows, and automate processes”
  • Showcase a track record of working with large datasets using SQL and Python
    — “Experience working with large datasets using code, including SQL and Python”
  • Emphasize your ability to work with non-technical stakeholders and translate complex data insights into actionable business strategies
    — “Strong ability to communicate with non-technical partners”
Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • leveraging AI to create scalable data tools
  • measuring and optimizing payments stack
  • serving as a subject-matter expert
Typical background
data scienceAIpayments

Skills & requirements

Required

AIData ToolsData-driven DecisionsCost EfficiencyRisk MitigationETL PipelinesMachine Learning Models

Preferred

Payments ExperienceBanking Experience

About the role

Original posting from Block (Square)

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 USDZone B: $106,100—$159,100 USDZone C:$100,500—$150,700 USDZone D:$95,000—$142,400 USDApplication Guidelines

Candidates may submit up to 9 active applications within a 60-day period. Reapplications to the same role are accepted 90 days after a previous application has been reviewed.

Use of AI in Our Hiring Process

We may use automated AI tools to evaluate job applications for efficiency and consistency. These tools comply with local regulations, including bias audits, and we handle all personal data in accordance with state and local privacy laws. 

Contact us here with hiring practice or data usage questions.

Every benefit we offer is designed with one goal: empowering you to do the best work of your career while building the life you want. Remote work, medical insurance, flexible time off, retirement savings plans, and modern family planning are just some of our offering. Check out our other benefits at Block.

Block, Inc. (NYSE: XYZ) builds technology to increase access to the global economy. Each of our brands unlocks different aspects of the economy for more people. Square makes commerce and financial services accessible to sellers. Cash App is the easy way to spend, send, and store money. Afterpay is transforming the way customers manage their spending over time. TIDAL is a music platform that empowers artists to thrive as entrepreneurs. Bitkey is a simple self-custody wallet built for bitcoin. Proto is a suite of bitcoin mining products and services. Together, we’re helping build a financial system that is open to everyone.

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Source: Block (Square) careers

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