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:

Underwriting and Credit

Our mission is to redefine credit and liquidity through simple, fair, and accessible credit solutions that build financial health and resilience.

You Will:

• Build and integrate 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
• Support multiple products across 4+ workstreams in Cash
• Empower teams 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
• 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

Qualifications

• Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related field. A Master’s degree is preferred
• 6+ years of experience in machine learning, data analysis, or a related field
• Strong knowledge of machine learning algorithms and data analysis techniques
• Excellent problem-solving skills and attention to detail
• Strong communication skills, with the ability to explain complex concepts to non-technical stakeholders
• Python (NumPy, Pandas, sklearn, xgboost, TensorFlow, keras, etc.)
• MySQL, Snowflake, GCP/AWS and Tableau