Machine Learning Modeler, Financial Crimes
- Full-time
- Alternate Location: Toronto, Canada
Company Description
Square is building two powerful eco systems to empower businesses and individuals financially.
Square Seller builds common business tools in unconventional ways so more people can start, run, and grow their businesses. Square has been building an entire business toolkit of both hardware and software products including Square Capital, Square Terminal, Square Payroll, and more. We’re working to find new and better ways to help businesses succeed on their own terms—and we’re looking for people like you to help shape tomorrow at Square.
Cash App’s mission is to serve the unbanked and completely disrupt traditional financial institutions and is currently the fastest growing financial brand in the world. Cash App has gone from a simple peer to peer payments product to a dynamic app with 30+ million monthly active users. We are bringing a better way to send, spend, invest, and save to anyone who has ever sought an alternative to the traditional banking system.
Job Description
The Financial Crimes Technology team at Square finds and reports financial crimes activity across Square products including Cash App and Seller tools. We work globally with partners in business, engineering, counsel and product to guarantee we are providing a safe user experience for our customers while minimizing or eliminating bad activity on our platform.
We are leveraging Machine Learning as an integral part of our toolkit to fulfil our mission. At Square scale, we are monitoring hundreds of billions of dollars in transactions across traditional payment and blockchain networks. We uncover and put an end to money laundering, fraud, and illegal activities before they impact our users. Additionally, we improve workflow and case tools, adding features that empower agent productivity and automate the high volume of monitoring.
You will:
- Build classification and anomaly detection models to detect criminal & unusual activity across Cash App’s p2p, banking, debit card, equities and crypto products
- Develop customer risk rating models that facilitate KYC at onboarding and ongoing basis for Square Sellers
- Leverage innovative features and state of the art algorithms to drive down false positives to improve agent productivity across Transaction Monitoring, Equities and Bitcoin Queues
- Join a new, small, and growing team and have a significant impact on influencing team culture and direction
- Use Python (numpy, pandas, sklearn, xgboost, Pytorch, TensorFlow, keras, plotnine etc.), MySQL, Snowflake, GCP, AWS for developing models
Qualifications
- 4+ years of Machine Learning and/or Deep Learning experience
- A graduate degree in computer science, data science, operations research, applied math, stats, physics, or a related technical field
- Experience with advanced techniques like word embeddings, sequence modeling, and graph convolutional networks is a big plus
- Experience working with product, business, and engineering to prioritize, scope, design, and deploy ML models
- Be able to communicate and influence business stakeholders
- Have a curious, passionate, growth-oriented mindset
Additional Information
Perks
At Square, we want you to be well and thrive. Our global benefits package includes:
- Healthcare coverage
- Retirement Plans
- Employee Stock Purchase Program
- Wellness perks
- Paid parental leave
- Paid time off
- Learning and Development resources