Payments Data Scientist – AI-Driven Analytics & Growth

Square; Seattle (WA); On-site; USD 111,000 - 167,000; Full time

Benefits offered by this job

Remote work

Medical insurance

Flexible time off

Retirement savings plan

Family planning support

Job summary

Block, Inc. (Square, Cash App) is seeking a data science professional focused on payments data to optimize the payments platform.

You will partner with Product, Operations, Finance, and Engineering to build scalable data tools and ML models and to drive data-driven decisions across the org. You will design experiments, build ETL pipelines, and maintain cloud data infrastructure while translating business needs into practical data solutions.

Qualifications

• Bachelor's degree in a quantitative field with strong academic record.
• Experience coding during an internship.
• Experience handling large datasets with SQL and Python.
• Experience using AI tools to accelerate development and automation.
• Strong analytical skills and business acumen.
• Ability to communicate with non-technical partners.
• Knowledge of systems architecture and cloud infrastructure.
• Bonus: experience in payments or banking.

Responsibilities

• Create scalable data tools, agents, and automations using AI.
• Collaborate with Product, Engineering, Finance, and Operations to data-drive decisions.
• Measure cost and performance of our payments stack.
• Design, run, and analyze experiments.
• Build ETL pipelines, dashboards, and ML models.
• Stand up, maintain, and improve cloud data infrastructure.
• Translate business needs into practical data solutions.

Skills

Bachelor's degree

Coding internship

SQL & Python

AI tooling

Analytical ability

Stakeholder communication

Cloud infrastructure

Payments knowledge

Education

Bachelor's degree in quantitative field

Tools

SQL

Python

Job description

Block, Inc. (Square, Cash App) is seeking a data science professional focused on payments data to optimize the payments platform.

You will partner with Product, Operations, Finance, and Engineering to build scalable data tools and ML models and to drive data-driven decisions across the org. You will design experiments, build ETL pipelines, and maintain cloud data infrastructure while translating business needs into practical data solutions.