Senior Machine Learning Modeler, Cash App
- San Francisco, CA, USA
- Employees can work remotely
- Alternate Location: Seattle, United States
Cash App is the fastest growing financial brand in the world. Initially 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 app with over 36 million monthly active users. We are bringing a better way to send, spend, invest, and save to anyone who has ever sought an alternative to the traditional banking system.
Loved by customers and pop culture, we’ve consistently held the top spot for finance in the App Store for many years, seeing more engagement with millions of followers across social media in a day than most brands see in a year. We are building an ecosystem to redefine the world’s relationship with money by making it universally accessible.
We want to hire the best talent regardless of location. Our employment model is distributed, offering the opportunity to collaborate with teams across the world in San Francisco, New York, St. Louis, Portland, Toronto, Kitchener-Waterloo, Sydney, and Melbourne.
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.
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:
A customer’s identity is the gateway for unlocking products, features, and higher limits in Cash App’s ever expanding ecosystem. With identity theft and fraud globally on the rise, it is becoming more and more important that financial companies like Cash App build confidence in who a customer says they are, especially when 100% of customer activity is done digitally. As part of the Identity Machine Learning team, you will work cross-functionally on analytical and ML solutions that help us build that confidence and trust in our customer base. Our goal is to reduce the friction good customers have throughout our onboarding and identity verification process while making it harder for bad actors to fake and/or steal someone else’s identity. Accomplishing this upstream before a customer ever takes a transaction means we can completely avoid any downstream fraud, good customer frustration, and/or work other teams have to deal with due to stolen identities.
You'll build machine learning models that detect fraudulent activity in real time and help keep our customers safe and secure. You will experiment with state-of-the-art algorithms to drive down false positives, collaborate on new product features to drive fraud losses down, use any and every dataset at your disposal (including 3rd party data) to engineer new features for risk models, verify customer documents using OCR, and use biometric and device signals to detect malicious logins and account takeovers.
Our Lending team works on models that drive marketing, pricing, and risk management for our consumer lending products. Through your work you will empower the team 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. You will 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. This role is best suited to someone with prior experience in the consumer credit or lending space.
Working closely with the Banking Product and Financial Platform teams, you will lead development of analytical and ML solutions that utilize our data to power optimizations across our Cash debit card and bank account products. Your work will aim to increase the customer adoption of banking products, reduce the manual operational load caused by banking features, and grow the overall revenue of Cash Banking as a whole. You'll be required to identify ML opportunities, prioritize your time, and solve complex problems where ML will have a significant impact for both our banking customers and/or the operation teams that support them.
Cash App enables millions of people and businesses to pay and get paid with ease. On our team, we build delightful experiences that help our customers find and discover each other quickly and with trust - we aim to grow and strengthen the connections between people and businesses across the globe. Through your work, you will empower Cash App to personalize customers’ search and discovery experiences using AI/ML, to better understand our customers’ payment journeys, and help identify and execute on new opportunities for product improvement. You will employ a variety of modeling techniques on our comprehensive customer data and scale your solution to production by partnering closely with design, product, analytics, and engineering teams. We are open to having remote members join for this position.
Customer Support Automation
Working closely with our Customer Support team, 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.
Technologies we use (and teach):
- Python (NumPy, Pandas, sklearn, xgboost, TensorFlow, keras, etc.)
- MySQL, Snowflake, GCP/AWS and Tableau
- 3+ years experience with applied Machine Learning or Deep Learning
- A graduate degree in Computer Science, AI, ML, Applied Math, Stats, Physics, or a related technical field
- Worked with Product, Design, and Engineering to prioritize, scope, design, and deploy ML models
- A track record of providing mentorship and technical leadership
- An appreciation for the connection between the software you build and the experience it delivers to customers
We’re working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Square is a proud equal opportunity employer. We work hard to evaluate all employees and job applicants consistently, without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible.
Additionally, we consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.
Square, Inc. (NYSE: SQ) builds tools to empower businesses and individuals to participate in the economy. Sellers use Square to reach buyers online and in person, manage their business, and access financing. Individuals use Cash App to spend, send, store, and invest money. And TIDAL is a global music and entertainment platform that expands Square's purpose of economic empowerment to artists. Square, Inc. has offices in the United States, Canada, Japan, Australia, Ireland, Spain, Norway, and the UK.