StyleSeat is the go-­to, marketplace destination for consumers to discover, book, and pay for beauty and grooming services (hair stylists, colorist, nail artists, estheticians, barbers, etc) from their phone. It is also the premiere solution for all independent professionals in the industry to run and grow their business.

Our professional community is diverse, 75% are women and 50% are minority-owned small businesses. We have powered over 100 million appointments booked and $5B in revenue for small businesses and are on the path to much more.

We are looking for a driven Data Scientist/Machine Learning Engineer to help take the StyleSeat experience to the next level of intelligence and joy. This role will work on core machine learning algorithms and systems that are part of our ability to understand the behavior and goals of our professional and client communities and build outstanding products. It will involve a wide variety of skills and innovation and is an unusual opportunity that sits at the cutting-edge of various engineering disciplines, and the work will have a huge impact on hundreds of millions of users across the US.

Roles and Responsibilities:

• Design, train, and deploy custom machine learning models for building search algorithms, pricing models and recommendation systems
• Deep experience with applying one or more major ML packages (e.g. TensorFlow, PyTorch) to very large data sets.
• Own and guide machine learning projects from conception through research, development and production deployment.
• Transfer machine learning solutions to engineers on product teams
• Explain and present machine learning concepts to a technical/non-technical audience
• Partner with other internal teams to identify opportunities in Product that can benefit from machine learning

The Candidate:

• 3+ years of experience in Machine Learning or Data Science field
• Collaborate and communicate cross-functionally with other engineering teams as well as business
• Experience designing, conducting, analyzing, and interpreting experiments and investigations.