Manager, Data Science, Marketplaces

About Carvana...

If you like disrupting the norm and are looking for a company revolutionizing an industry then you will LOVE what Carvana has done for the car buying experience. Buying a car the old fashioned way sucks and we are working hard to make it NOT suck. At Carvana, our customers can hop online to...

• Search and browse our inventory of over 20,000 vehicles that we own and certify.
• Narrow down search results using highly intelligent filtering tools/components.
• View vehicle details, Carfax reports, and 360 rotating studio images for every vehicle.
• Secure financing in minutes using Carvana’s in-house service or their own bank.
• Interact with GUI components to easily customize loan length, down payment, and monthly payment.
• Generate, upload, and eSign all documents online (no ink necessary).
• Schedule front door delivery or pick up at one of our vending machines.
• Trade-in their existing vehicle or just sell it to Carvana (no purchase necessary).

We’ve been changing the game since 2013, and we’re not taking our foot off the gas now. Here are a few of our stories!  

THIS IS A 100% ON-SITE POSITION (Monday through Friday)

About the team and position

In today’s world, data is king and this is the team with all the data. If you’re excited about understanding complex data sets from disparate sources, this is the team for you. Our data science and analytics team automates everything Carvana does from modeling consumer behavior to understanding how to make our users’ lives better. 

In order for all of this to work, we must understand the market for used cars. We act not only as a buyer, but through our marketplaces provide services for dealers, lenders, and automotive companies to best position them in maximizing their goals.  This position will involve deep focus on our wholesale marketplace business and the underlying predictive models, optimization frameworks, and automation capabilities. Our solutions integrate multiple predictive models and interoperate with pricing, reconditioning, and assortment optimization frameworks to drive the best B2B marketplace experiences.  

What you’ll be doing

• Leading a team of Data Scientists to build and productionalize modeling products through all stages of development from ideation to model maintenance and measurement of results.
• Working closely with our senior leaders in Product, Experience, and Software Engineering teams to deliver impact on every aspect of the transaction processes, from search to vehicle delivery. 
• Building and extending predictive models related to vehicle demand, reconditioning expenses, bid win probabilities, recommendation engines, and total transaction value.
• Building simulation capabilities to predict win volume vs. bidding policy in upcoming vehicle auctions.
• Analyzing tradeoffs between inventory diversity and wholesale auction availability in optimizing assortment.
• Improving bidding optimization policy to drive improvements in KPIs related to profitability and turn times.
• Analyzing regional / geographic variations in supply and demand
• Utilizing data and rigorous analytical methods to drive decision-making across all areas of the business including purchasing, pricing, inventory control, demand modeling and forecasting, product mix optimization, and logistics.
• Working with multiple valuation sources related to retail and wholesale vehicle pricing.
• Using market data to analyze wholesale/retail assortment and pricing vs. market competition.
• Other duties as assigned.

What you should have

• Degree in Data Science, Engineering, Applied Math, Operations Research, Computer Science, Statistics, Econometrics
• 5+ years of experience managing sophisticated analytics and data science teams.
• Thorough understanding of machine learning algorithms, tools, and techniques.
• Deep understanding and experience in one or more of the following topics: Optimal Control, Dynamical Systems Theory, Nonlinear optimization, Reinforcement Learning, Neural Networks, Monte Carlo Methods, Discrete Event Simulation, Bayesian Inference, Time Series Analysis, Portfolio Optimization
• Experience in applying one or more of the above techniques to practical business problems in supply chain, pricing, revenue management, and/or inventory control settings
• Experience in developing production-quality code (Python, R) is a plus.
• Strong fluency in SQL and OLTP databases.
• Strong understanding of statistics and data mining methods
• Experience with lar