Remote Payments Data Scientist - AI & Analytics

Block; San Francisco (CA); On-site; USD 112,000 - 168,000; Full time

Benefits offered by this job

Remote work

Medical insurance

Flexible time off

Retirement plans

Family planning

Job summary

Block is seeking a quantitative, AI-fluent data science early-career professional to optimize payments data across Square and Cash App. You will partner with Product, Operations, Finance, and Engineering to build scalable data tools, run experiments, and deliver data-driven decisions that improve success rates, cost efficiency, and risk mitigation.

You will design ETL pipelines, dashboards, and ML models, translate business needs into data solutions, and work across the Data Org on systems,

Qualifications

• Bachelor's degree in a quantitative field
• Experience with code during an internship
• Experience with large datasets using SQL and Python
• Experience using AI tools to accelerate development and automate workflows
• Strong analytical skills and business acumen
• Strong communication with non-technical partners
• Knowledge of systems architecture and cloud infrastructure
• Bonus: payments or banking experience

Responsibilities

• Design, run, and analyze experiments to drive data-backed decisions
• Build ETL pipelines and dashboards for payments data
• Develop scalable data tools, agents, and automations with AI
• Partner with Product, Engineering, Finance, and Operations to improve the payments stack
• Measure cost and performance of the payments platform
• Translate business needs into practical data solutions
• Maintain data systems and cloud infrastructure
• Research questions and produce actionable insights

Skills

SQL

Python

AI tools

Data analysis

Communication

Cloud infrastructure

Systems architecture

Education

Bachelor's degree in a quantitative field

Tools

SQL

Python

AI tools

Job description

Block is seeking a quantitative, AI-fluent data science early-career professional to optimize payments data across Square and Cash App. You will partner with Product, Operations, Finance, and Engineering to build scalable data tools, run experiments, and deliver data-driven decisions that improve success rates, cost efficiency, and risk mitigation.

You will design ETL pipelines, dashboards, and ML models, translate business needs into data solutions, and work across the Data Org on systems,