Data Science Lead, Cash App
- San Francisco, CA, USA
- Current Square Employee?: Apply via go/jobs
We are looking for data science leaders to join Square and help build Cash App, the fastest growing financial app in the world. Machine Learning is an integral part of how we design products, operate, and pursue Cash App’s mission to serve the unbanked and completely disrupt traditional financial institutions. Our massive scale and rich transaction data create an endless number of opportunities to use AI 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.
As a data science lead you will partner with one of our many product teams, collaborate on strategy and roadmaps, and apply machine learning to our products in new, innovative ways. The role will be hands on while leading and hiring other data scientists to work for and alongside you. This role reports directly to Cash App’s Head of Data Science. We are currently looking for:
Data Science Lead, Customer Support
Working closely with our Customer Support product and operations teams, you will use our vast amounts of data to make experiences seamless for our customers and help us achieve world-class service as Cash App continues its rapid growth. 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.
Data Science Lead, Network (P2P)
Working closely with our Network product team, you will research the virality of our P2P network and build predictive models that fuel growth. You will use our proprietary P2P payment graph to improve customer search, use NLP to understand how customers transact with each other, study price sensitivity to drive engagement with our instant deposit feature, and invent new data products that enrich the P2P experience between friends and family.
Data Science Lead, Banking
Working closely with our Banking product team, you will develop algorithms and tools that help customers understand their financial health as well as assist in their financial planning and decision making. You will develop in-house transaction authorization models, predict customer income via direct deposit transactions, classify card transaction data to better understand customer spending patterns, alert customers about upcoming bill payments, design personalized fee-less overdraft limits, and apply computer vision to digital debit card signatures.
3-5 years of relevant industry experience
A graduate degree in computer science, AI, ML, applied math, stats, physics, or a related technical field.
A track record of providing mentorship and technical leadership
Experience working with product, design, and engineering to prioritize, scope, design, and deploy ML models
An appreciation for the connection between the software you build and the experience it delivers to customers
A strong desire to perform and grow as a people lead, scientist, and/or engineer
Technologies we use and teach
Python (numpy, pandas, sklearn, xgboost, TensorFlow, etc.)
MySQL, Snowflake, GCP, AWS, Tableau
Fair and square
At Square, we value diversity and treat all employees and applicants based on merit, qualifications, competence 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.
All your information will be kept confidential according to EEO guidelines.
At Square, our purpose is to empower – within and outside of our walls. In order to build the best tools for the businesses and customers we support all over the world, we have to start at home with a workforce as diverse and empowered as our sellers. To this end, we take great care to evaluate all employees and job applicants equally, based on merit, competence, and qualifications. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. We encourage candidates from all backgrounds to apply and always consider qualified applicants with arrest and conviction records, in accordance with the San Francisco Fair Chance Ordinance. Applicants in need of special assistance or accommodation during the interview process or in accessing our website may contact us by sending an email to assistance(at)squareup.com. We will treat your request as confidentially as possible. In your email, please include your name and preferred method of contact, and we will respond as soon as possible.