Senior Data Scientist, Risk
Listed on 2026-07-25
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IT/Tech
Machine Learning/ ML Engineer, Data Analyst, Data Scientist, Data Science Manager
Job Description Company Description
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 through Afterpay, 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.
We are seeking a rock star Senior Data Scientist to join our Risk Data team within the Ecosystem Fraud Team will play a pivotal role in combating high-risk fraud and scams across our platform, utilizing advanced machine learning and analytical solutions. This position involves end-to-end project ownership, from feature identification to deployment and real-time fraud mitigation.
Key ResponsibilitiesFraud Detection & Prevention:
Develop processes to identify and mitigate high-risk fraud and scam activities.
Analyze and deploy solutions to real-time Square systems to prevent fraud in real-time.
Data Analysis & Feature Development:
Identify and analyze new fraud detection features using SQL, Databricks, and Python.
Build real-time features and implement them effectively.
Model Building & Machine Learning:
Collaborate with ML engineers to develop and leverage machine learning models.
Engage in ML model building activities for fraud detection (approximately 20% of the role).
Ad Hoc Fraud Mitigation:
Respond to and mitigate real-time fraud attacks as they occur.
Reporting & Dashboard Creation:
Create and maintain dashboards to monitor key metrics and operational KPIs.
Develop comprehensive reporting dashboards for internal use.
Cross-functional Collaboration:
Work closely with Product Managers, Engineers, Operations, and Policy teams.
Take projects from conceptualization to execution with minimal supervision.
Statistical Testing & Efficiency Monitoring:
Conduct statistical tests to evaluate the effectiveness of various initiatives.
ETL & Data Pipeline Management:
Create and maintain ETLs and data pipelines for continuous data integration and analysis.
Leadership & Presentation Development:
Develop and deliver presentations to Square leadership on fraud detection strategies and outcomes.
You Have:
A passion for Square's mission
5+ years of relevant experience (or masters degree with 3+ years of experience)
Self-motivated and able to manage projects from start to finish with minimal supervision
Strong analytical and problem-solving skills
High proficiency in SQL and Python
Familiarity with AWS, GCP, Databricks, Github, Airflow and Looker
Proven ability to collaborate effectively with cross-functional teams
Experience in risk, trust and safety, payments, or spam prevention
Join us in making a significant impact by ensuring the safety and integrity of Square's platform through innovative fraud detection and prevention strategies.
Additional InformationBlock 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.…
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