Data Science Manager, Cash App
- San Francisco, CA, USA
- Employees can work remotely
- Position open to remote: Yes
- Current Square Employee?: Apply via go/jobs with your Square email.
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, 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 a Data Science Manager to join our team and help continue to build Cash App. You will report to the Head of Data Science & Analytics and oversee our Financial Platform worksteam. You and your team will develop the core platforms that our application runs on, optimizing user experience for each Cash product, building for long-term scalability and working to understand the potential of different networks we've acquired or invested in. Although this is a leadership role, we want someone who brings technical depth - you should expect an interview process which optimizes for both leadership and technical skills. This is a relatively new discipline and organization at Cash App, and we will be really focused on managing the transition from a nascent team to a vision state and pushing the team from a reactive model to driving insights.
- Lead a team of 5 Data Scientists to start and quickly scale up
- Create a unique vision and approach for this team how they collaborate, set goals, and scale
- Partner with senior leaders from different teams: Business Operations, Engineering, Machine Learning, Compliance/Reporting, Reconciliation and BI Engineering
- Offer technical mentorship to existing team members, focusing on their long-term growth
- Work with your partners to:
- Establish rituals for product quality and functionality funnel analysis with the broader FinPlat team
- Automate away core reporting together with our BI engineering team
- Establish a regular rhythm of delivery for research and insights to the business
To be successful, you should have:
- 3+ years of experience as a Manager of Data Scientists, Analysts, or Applied Researchers
- A background/advanced degree in Stats, Physics, Economics, or another STEM field would likely be useful, but we're open - your applied work in DS over the past few years will be way more of a factor
- Enough (and recent) proficiency with Python, SQL and other relevant tools that will allow you to support and mentor the team and encourage their technical growth
- Experience working with and mentoring others on a variety of problem types including:
- Modeling for analytic and POC purposes (rather than just for production use cases)
- Cohort and funnel analyses
- Testing and experimentation including statistical concepts such as selection bias, probability distributions, and conditional probabilities
- Building, forecasting and reporting on business/product metrics and visualizations
- Data sourcing and ETL work
- Contract negotiations
- A connection to our vision of economic empowerment and work to understand the struggles of the customers we're building products for - if you want an example of who we think about for new products, read the first 10 pages of this book
Technologies we use and teach:
- SQL (MySQL, Snowflake, BigQuery)
- Python and packages like Pandas, NumPy and sklearn
- Tableau, Airflow and Looker
Cash App treats all employees and job applicants equally. Every decision is based on merit, qualifications, and talent. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will consider for employment qualified applicants with criminal histories in a manner consistent with each office’s corresponding state and city guidelines.