At Hopper, we’re on a mission to build the most customer-centric travel company on earth. We are leveraging the power that comes from combining massive amounts of data and machine learning to build the world’s fastest-growing mobile first travel marketplace -- one that enables our customers to save money and travel better.
Hopper’s goal is to reduce traveler anxiety throughout all stages of the trip buying and taking process. By creating a transparent travel marketplace and unique, data-driven financial technology products focused on providing peace-of-mind, Hopper adds value along each step of the customer’s journey.
Hopper has launched several bespoke fintech products that leverage our immense first and third-party data to create products and value that do not exist elsewhere - including Refundable and Flexible Tickets and Price Freeze. Thanks to these offerings, Hopper’s revenue growth is up 112% despite the travel slowdown due to COVID-19.
With over $250M CAD in funding from leading investors in both Canada and the US, Hopper is primed to continue its acceleration to becoming the world’s fastest-growing end-to-end customer-centric travel offering.
Recognized as one of the world’s most innovative companies by Fast Company three years in a row, Hopper has been downloaded over 50 million times and sees over 1 million new installs per month. The app has received high praise in the form of mobile accolades such as the Webby Award for Best Travel App of 2019.
Come take off with us!
We’re looking for a motivated research scientist experienced in the intersection of operations research and data science to help us build flight search optimization algorithms to solve complex travel planning and pricing problems. This is an opportunity to have a massive impact: you will be the first operations research scientist on this team dedicated to building a sophisticated fare construction engine.
Hopper was built on the premise that the combination of big data + machine learning could empower travelers in a completely unprecedented way. We collect 30 billion airfare quotes every day from flight searches happening across the web, with about six years of historical data, so we can track prices, measure interest, and ultimately detect price trends to know when is the best time to buy. We now want to leverage this vast data infrastructure to make travel more accessible for our customers by offering a more robust, unique, and cheaper flight inventory selection that users cannot find elsewhere. As an operations research scientist, you will achieve this goal by building smart search algorithms that can dynamically predict the best possible route combinations for any given user search from A to B.
Hopper did about $1B in sales last year and is weathering the COVID storm better than one would expect. We just raised $70M and even in these challenging times we're actually capturing market share and will be YoY positive on revenue.
Now we need to lay the groundwork for a growth-centric year in 2021 by building a great team that can help us compete with the travel giants. As such, you will be joining a cross-functional and collaborative team composed of business, product, and engineering leaders that are entirely focused on solving the challenge of search and fare optimization, as it is one of the largest opportunities for growth that Hopper has as a company. This role is a crucial part of ensuring our success.
IN THIS ROLE, YOU WILL:
- Frame and conduct complex exploratory analyses needed to deepen our understanding of this problem and guide our solution design.
- Employ advanced mathematical and analytical methods to help us make smarter flight shopping decisions and create better inventory.
- Design and build working prototypes of your models to test and iterate on in production.
- Partner with engineering to deploy your algorithms in production and help guide backend infrastructure requirements.
- Find effective ways to simplify and communicate applied research work to technical and non-technical audiences.
A PERFECT CANDIDATE HAS:
- An advanced degree in Applied Math, Statistics, Computer Science, Engineering or other quantitative disciplines
- Experience with data mining, combinatorial optimization, machine learning, statistical modeling tools and underlying algorithms
- A strong background in computer science and complex data structures
- Experience in C++, Python or other tools appropriate for large scale data modeling and analysis
- Experience with relational databases and SQL, including geographical and/or airline data
- Proven ability to communicate complex technical work to a non-technical audience
- Extremely strong analytical and problem-solving skills
- A strong passion for and extensive experience in conducting empirical research and answering hard questions with data
- Experience in operations research applied to the transportation or logistics industry (nice to have)
• Well-funded and proven startup with large ambitions, competitive salary and stock options
• Dynamic and entrepreneurial team where pushing limits is everyday business
• 100% employer paid medical, dental, vision, disability and life insurance plans
• Access to a 401k (US) or Retirement Savings Plan (Canada)