Job Description

The Square Financial Crimes Machine Learning team is responsible for detecting, preventing, and reporting illegal activity across all markets in which Square operates. We work globally with partners in business, engineering, counsel and product to ensure we are providing a safe user experience for our customers while minimizing or eliminating bad activity on our platform.

We leverage Machine Learning as an integral part of our toolkit to fulfill our mission. We employ scalable solutions in order to monitor billions of dollars in transactions. We uncover and put an end to money laundering, terrorist financing, and other illegal activities before they impact our users. Additionally, we improve workflow and case tools, adding features that empower investigator productivity and automate the high volume of monitoring. We are looking for senior MLEs who are interested in solving critical business problems using any and all tools necessary.

You will:

• Build both batch and real-time machine learning solutions for the assessment of financial crimes risk at scale across all global markets in which Square operates
• Work closely with stakeholders, business partners, and product engineering teams to ensure that data can be leveraged effectively to build efficient solutions within our regulatory program
• Produce thorough documentation of our program that can withstand regulatory scrutiny
• Proactively identify new opportunities and future needs of our ML teams
• Lead by example by applying ML and engineering best practices
• Stay current on ML developments in the field, foster an environment of continuous learning, and apply new learnings when applicable
• Have a significant impact on influencing team culture and direction

Qualifications

You Have: 

• 5+ years of software engineering or machine learning experience
• A degree (preferable graduate level) in Computer Science, Engineering, Statistics, Physics, Applied Math or a related technical field
• An ability to maintain critical production software and build new production software from scratch
• Prior experience working with product, engineering, and business to prioritize, scope, design, and deploy ML tooling and infrastructure at scale
• Natural curiosity and desire to grow and help shape all aspects of our small and growing team
• Excellent written and oral communication skills and are comfortable working with a cross-functional, globally distributed team