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!

This role is part of Cash App’s Risk ML team and will be embedded within one of the below workstreams:

Identity: Using machine learning methods and systems, this team reduces the prevalence of inauthentic identities in Cash’s ecosystem, provides a first line of defense against bad actors attempting to circumvent our IDV controls while simultaneously building our confidence in existing and new customers’ identities. Our goal is to ensure that every individual has access to the financial services they need, regardless of their background or financial history. We believe that ML has the potential to revolutionize the way in which identity verification is conducted, and we are dedicated to constantly improving and refining our solutions to ensure that it remains at the forefront of this rapidly evolving field. By using machine learning for identity verification, we aim to create a safer and more inclusive financial system for all.

Cash Card + Disputes: This team owns analytical and ML solutions for the full lifecycle of the Cash Card product with a focus on mitigating risk/fraud. Team works cross-functionally with Product, Platform, Legal, and others to balance financial loss to the business, regulatory risk, and the holistic customer experience.

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