Overview of Position

Varsity Tutors believes access to quality education is critical for everyone to achieve their goals. Leveraging AI and professional educators Varsity Tutors makes quality, personalized education accessible wherever and whenever you need. To date, students have accessed more than three million hours of live instruction on the platform. Experts are available to meet in person or through the company’s award-winning online and mobile platforms. Our vision is to seamlessly connect experts and learners in any subject, anywhere, anytime.

We are looking for problem solvers with mastery in analytics, statistics and machine learning to join the Data Science team at Varsity Tutors. This team partners with product and engineering to enable real-time decisions, forecasting, resource optimization, and other applied solutions.

The qualified candidate will hold an advanced quantitative degree with applied experience in achieving business results through mathematical analysis. The candidate is also expected to be comfortable developing dynamic prototypes that can be productized by engineering to develop production systems. Candidates must be comfortable with pushing through ambiguity and passionate about solving problems across a variety of domains at scale and with speed.

About Varsity Tutors:

Varsity Tutors, a Nerdy Company, is the leading direct-to-consumer, curated gig economy platform for live online learning benefiting both learners and experts. We have built a comprehensive online learning destination that enables the delivery of scaled high-quality live expertise for learners of all ages across thousands of subjects and multiple learning formats through the application of technology and AI. We've raised $107M million in venture capital from TCV, Learn Capital, and the Chan Zuckerberg Initiative. We also recently announced that Nerdy, the parent company of Varsity Tutors, plans to go public via a SPAC with TPG Pace Tech Opportunities later this year, with a $1.7 billion market valuation.

Qualification:

• Develop machine learning models for classification, segmentation, multivariate regression, etc, to develop data products for forecasting market level dynamics, optimizing operational flows, and encoding a broad knowledge base across hundreds of subject domains.
• Design experiments and prototype simple or complex algorithms and partner with product, operations and engineering to implement in production.
• Develop methods to help users understand and use predictive models.

Requirements: 

• Strong quantitative background; M.S. or Ph.D. degree preferred.
• Experience with one or more of the following: Bayesian reasoning, Natural Language Processing, speech processing, computer vision, classification, ranking systems, recommendation systems, linear or constraint optimization.  
• Solid data engineering skills.
• Experience with machine learning software packages ( e.g. PyTorch or TensorFlow, scikit-learn, etc. (INDHP)