Sr. Data Scientist, Machine Learning - Varo Money

Job Title: Sr. Data Scientist, Machine Learning
Job Location: San Francisco, CA
Job Listing URL: https://jobs.lever.co/varomoney/52fd8221-1511-4c0b-a3b8-3b604ea6d58e
Job Description: Varo is an entirely new kind of bank. All digital, mission-driven, FDIC insured and designed for the way our customers live their lives. A bank for all of us.

About The Role
Varo represents a new generation of fintech built on technology and innovation to empower consumers. We serve millions of Americans with our mobile app to make digital banking easy, convenient, and personalized. As a Senior Data Scientist (Machine Learning), you’ll get the chance to develop innovative models that affect millions of users in the fintech space. You’ll work with experienced Machine Learning Scientists as well as collaborate with your peers on exciting science problems in the fraud detection, risk modeling, personalization, operations, and causal inference spaces.

About the Data Science Team
Varo’s Data Science Team develops Machine Learning models that make it easier for the right people to get access to funds, help protect customers from fraudsters, and transform the in-app experience with real-time recommendations. Unlike some organizations where data takes a support role, here at Varo data science is front and center. Since we are in hyper-growth mode, you will get to work on the most impactful data science problems from day one. We rely on advanced techniques in machine learning, cloud platforms, and data technology. We’re a team of PhDs and ex-academics with a collegial work atmosphere. If you are interested in working with an impressive team of Data pros who collaborate and challenge each other and want to solve interesting problems to propel the company’s growth, apply now!
What you'll be doing
Develop production-grade ML algorithms, such as fraud detection algorithms, recommender systems, dynamic credit risk models, and large-scale causal inference models, as well as processes for monitoring and analyzing their performance
Leverage large data sets from different sources, and use modern modeling techniques such as tree-based methods, neural networks, and reinforcement learning to increase and optimize customer experiences, customer acquisition, underwriting, and other business outcomes
Work with stakeholders throughout the organization to identify opportunities for driving business decisions or improving our product suite with ML
Collaborate cross-functionally with the engineering team to deploy models and monitor outcomes
You’ll bring the following required skills and experiences
An advanced degree in a quantitative field - computer science, engineering, statistics, operations research, economics, etc.
4+ years of experience as a Data Scientist, Machine Learning Scientist, or Research Scientist as an individual contributor, including but not limited to relevant experience from your PhD research
Experience applying a wide range of statistical techniques to large data sets, and understanding their real-world advantages/drawbacks
Experienced in using Python for analysis, modeling, and visualization (numpy, pandas, scikit, nltk, matplotlib, etc.)
Ability to thrive in a fast-paced environment
Strong bias for action and team player
Preferred: Familiarity with Sagemaker, Spark, TensorFlow, Keras, and PyTorch