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!
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. At Varo, we believe the future of fraud detection in fintech lies with Machine Learning. We are innovating models that dynamically calculate fraud risk scores and predict customer transaction behavior. You’ll lead Machine Learning in Fraud at Varo, working on models that protect customers from fraudsters while growing Varo’s customer base and enabling product features to be more accessible to all. You will be responsible for developing the machine learning models that will underlie Varo’s fraud detection system. You will own the development and training of these models, as well as contribute to the design of architecture that serves the models.
What you'll be doing
Lead efforts within the organization to drive the design, development, optimization, and productionization of ML-based fraud models
Enable customers to have broader access to risky product features by designing a fraud system that balances precision of detection with customer experience and growth
Work with stakeholders in the fraud organization to identify opportunities for driving business value with ML
Collaborate cross-functionally with the engineering team to deploy models and monitor outcomes
Guide and mentor junior machine learning scientists and engineers
You’ll bring the following required skills and experiences
4+ years of expertise in developing ML industry applications for fraud or risk applications
Demonstrated experience and/or interest in building fraud detection machine learning models
Ph.D. or equivalent in Computer Science, Statistics, or related field
Strong bias for action and team player
Ability to thrive in a fast-paced environment
Preferred: Familiarity with Sagemaker, Spark, TensorFlow, Keras, and PyTorch