Job Description

Machine Learning is an integral part of how we design products, operate, and pursue Cash App’s mission to serve the unbanked as well as disrupt traditional financial institutions. Our massive scale and deep trove of transaction data create an endless number of opportunities to use artificial intelligence to better understand our customers and offer new products and experiences that can improve their lives. We are a highly creative group that prefers to solve problems from first principles; we move quickly, make incremental changes, and deploy to production every day. Check out our Machine Learning / AI blog here!

This role is part of our Cash App’s ML team and will be deeply embedded within one of our product teams - here are the workstreams we’re currently hiring for:

Health

You’ll build machine learning models that detect fraudulent activity in real time and help keep our customers safe and secure. You will experiment with state-of-the-art algorithms to drive down false positives, collaborate on new product features to drive fraud losses down, use any and every dataset at your disposal (including 3rd party data) to engineer new features for risk models, verify customer documents using OCR, and use biometric and device signals to detect malicious logins and account takeovers.

Customer Support Automation

We aim to create better-than-human Customer Support Experiences. Cash App holds people’s money, and building customers’ trust is absolutely essential to our brand. Providing fast and reliable help whenever the customer needs it is a major component of building that trust. You will build models that anticipate customer issues and deliver proactive in-app suggestions, use NLP to contextualize inquiries and respond instantly with relevant content, develop prioritization algorithms that improve efficiency, and apply the latest research to automate conversations with customers.

Underwriting and Credit

Our mission is to redefine credit and liquidity through simple, fair, and accessible credit solutions that build financial health and resilience. This team builds and integrates ML solutions for evaluating customer cash flow risk including risk of default on credit obligations, risk of fraud & abuse of loans and other situations where Cash app advances funds or provides liquidity to customers. We support multiple products across 4+ workstreams in Cash. Through your work you will empower the team to understand the financial performance of origination cohorts, optimize our automated decisioning pipeline using AI/ML, and help identify new opportunities for growth in our customer base. You will experiment with various modeling techniques on our comprehensive customer data and see your solution through to production by partnering cross-functionally with finance, product, and engineering teams.

Commerce Fraud Risk

Afterpay is the largest Buy Now, Pay Later (BNPL) product by market share in Australia and continues to experience rapid growth in the United States. Throughout this journey, we encounter risks and challenges from various aspects. The Commerce Fraud and Merchant Risk Team utilizes cutting-edge modeling technologies to effectively mitigate both fraud and merchant risks. Simultaneously, we collaborate with highly efficient product and development teams to continuously build and enhance a competitive risk management engine within the industry.

Technologies we use (and teach):

• Python (NumPy, Pandas, sklearn, xgboost, TensorFlow, keras, etc.)
• MySQL, Snowflake, GCP/AWS and Tableau
• Java

Qualifications

You have:

• 5+ years experience with applied Machine Learning or Deep Learning
• A graduate degree in Computer Science, AI, ML, Applied Math, Stats, Physics, or a related technical field
• Worked with Product, Design, and Engineering to prioritize, scope, design, and deploy ML models
• A track record of providing mentorship and technical leadership
• An appreciation for the connection between the software you build and the experience it delivers to customers