Data Science Lead, Operations
- Full-time
Company Description
Job Description
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.
You will:
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
Qualifications
You have:
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)
MySQL, Hive
Java
Google Cloud Platform
Tableau, Looker