Data Science Lead, Operations
- San Francisco, CA
We believe the economy is better when everyone has access. When everyone has room to grow. No one should be left out because the cost is too great or the technology too complex. We started with a little white credit card reader but haven’t stopped there. We’re empowering the independent electrician to send invoices, setting up the favorite food truck with a delivery option, helping the ice cream shop pay its employees, and giving the burgeoning coffee chain capital for a second, third, and fourth location. We’re here to help sellers of all sizes start, run, and grow their business—and helping them grow their business is good business for everyone.
The Operations Data Science team is part of Square’s Payments Platform. As the lead for Operations Data Science, you will be responsible for leading a team of data scientists and product analysts in optimizing the Customer Success experience, as well as detecting and preventing money laundering. In both cases, you will ship solutions that improve the lives of Square’s merchants and the agents that serve them every day.
We’re looking for an inquisitive, metrics-driven, empathetic leader that is not afraid of challenging assumptions, diving into the data, and double checking results.
Drive cross-functional data science projects from beginning to end: Build relationships with partner teams, frame and structure questions, collect and analyze data, and summarize and present key insights in support of decision making
Lead your team of Data Scientists and Product Analysts in detecting and preventing money laundering.
Lead your team of Data Scientists and Product Analysts in optimizing an operations team responsible for fielding Customer Success inquiries and investigating money laundering
Set the team roadmap and develop technical strategy to fulfill the team mission
Recruit, motivate, and train data scientists and product analysts
A graduate degree in computer science, AI, ML, applied math, stats, physics, or a related technical field.
Experience working with product, design, and engineering to prioritize, scope, design, and deploy ML models
A track record of providing mentorship and technical leadership
The versatility to communicate clearly with both technical and non-technical audiences
A strong desire to perform and grow as a people lead, scientist, and/or engineer
Efficiency: Excellent organizational and prioritization skills as demonstrated by experience autonomously driving multiple, competing projects under deadline pressure
Enthusiasm: You’re passionate about Square’s mission and are willing to learn new technologies on the job
Technologies we use and teach:
Python (numpy, pandas, sklearn, xgboost, TensorFlow)
Google Cloud Platform
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. Perks At Square, we want you to be well and thrive. Our global benefits package includes: Healthcare coverage, Retirement Plans, Employee Stock Purchase Program, Meal reimbursements, Wellness perks, Paid parental leave, Flexible time off, Learning and Development resources