About the job:
Cash App is the fastest growing financial brand in the world. Built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic money app with over 30 million active monthly users.
Loved by customers and by pop culture, we’ve held the #1 spot in finance on the App Store for almost two years, and our social media posts see more engagement in a day than most financial brands see in a year.
With major offices in San Francisco, New York, St. Louis, Portland, Kitchener-Waterloo, Toronto and Melbourne, Cash App is bringing a better way to send, spend, and save to anyone who has ever sought an alternative to today’s banking system.
We are looking for an experienced engineering manager to join our Growth Machine Learning team and help build Cash App. The Growth ML team uses our large and unique datasets to model, understand, and predict customer behavior to help optimize customer acquisition, engagement, retention, personalization, and more.
This role is a part of the broader ML team and will report directly to the head of the organization. Partnering closely with our Growth product team, you’ll work with them to ideate projects and deliver value to our customers through the use of applied machine learning. You will also collaborate with the members of your team to identify new and large opportunities that will shape the Growth roadmap. We are looking for someone who will thrive in a fast-paced environment and will be hands-on when needed.
- Recruit, lead, and mentor a strong team (current team size of 4, with future growth planned)
- Dive deeply with members of your team to provide coaching that ensures their success, providing hands-on technical guidance and direction in critical high-impact areas as needed
- Partner and collaborate closely with Cash App’s product and business leaders
- Work cross-functionally with product, platform, and data engineering teams to prioritize efforts that will bring your team’s work to life Identify new opportunities, develop prototypes, achieve buy-in from partners, and communicate staffing needs
- Effectively communicate your team’s work with senior leadership and the executive team on a regular basis
- Stay up-to-date with the latest state-of-the-art techniques in machine learning and foster a culture of learning within the organization
- Help shape Cash App’s ML and Growth strategies
- Strategically develop an operating thesis of the machine learning algorithm capabilities, software, and team against the goals of the organization. Specifically, how we can compound “reusable leverage” to guide a broader impact with “AI, first” software
- Partner closely with product managers, engineers, and organizational leadership to establish your team’s vision and roadmap by thoroughly understanding your customers’ needs
- Have an “owner and operator” mentality of evolving artificial intelligence driven products
- Build products, systems, and services that have immediate impact on our customers that are operated by machine learning, specifically modern deep learning architectures.
- Lead technical, design, and product discussions with other leaders across the organization and company and promote a machine learning development lifecycle culture within the team
- Experience leading teams both technically and in a formal management capacity
- Expertise in applying machine learning to solve large, complex business problems in a production setting
- Deep knowledge of and experience with a range of machine learning algorithms and techniques
- Strong software engineering fundamentals and the ability to write production code when needed (your interview process is going to include pairing sessions)
- Strong statistical and mathematical intuition with an appreciation for concepts such as causality, selection bias, incrementality, hypothesis testing, etc.
- Experience working with a Growth team in a fast-paced high-growth tech environment Intellectual curiosity and a passion for Cash App’s mission of economic empowerment
Technologies we use and teach:
- Python (and its machine learning and data analysis libraries/frameworks)
- SQL (Snowflake), Airflow, Tableau