Job Post

Data Scientist

Hopper
275 Third Street
Cambridge, MA 02142

About Hopper

At Hopper, were on a mission to make booking travel faster, easier, and more transparent. We are leveraging the power that comes from combining massive amounts of data and machine learning to build the worlds fastest-growing travel app -- one that enables our customers to save money and travel more. With over $235M CAD in funding from leading investors in both Canada and the US, Hopper is primed to continue its path toward becoming the go-to way to book travel as the world continues its shift to mobile.

Recognized as the fastest-growing travel app by Forbes and one of the worlds most innovative companies by Fast Company two years in a row, Hopper has been downloaded over 35 million times and has helped travelers plan over 100 million trips and counting. The app has received high praise in the form of mobile accolades such as the Google Play Award for Standout Startup of 2016 and Apples App Store Best of 2015.

Take off with us!

The Role

At Hopper, every dataset tells a story. Do you have what it takes to decipher the clues? bit.ly/2q6U8dq

Were looking for a data-savvy individual to join our team as a data scientist, to support data-centric product development and create consumer-focused research content based on our real-time feed of billions of flight search results along with an archive of several trillion data points.

You may be a great fit for our team if you are excited about exploring huge (and sometimes messy) data sets and finding effective ways to simplify and communicate the results to a non-technical audience.

In this role you will:

  • Frame and conduct complex exploratory analyses needed to deepen our understanding of our users. Partner with product, business and strategy teams to contribute to product improvements and initiatives.
  • Use machine learning and big data tools on tremendously large and complex data to deepen our data-driven advice and personalized modeling.
  • Conduct research into various aspects of our business and employ statistical and modeling techniques when appropriate to make recommendations to non-technical stakeholders.

A perfect candidate has:

  • A degree in Math, Statistics, Computer Science, Engineering or other quantitative disciplines
  • Extremely strong analytical and problem-solving skills
  • Proven ability to communicate complex technical work to a non-technical audience
  • A strong passion for and extensive experience in conducting empirical research and answering hard questions with data
  • Experience with relational databases and SQL, especially Hive
  • Experience working with extremely large data sets
  • Experience in Pandas, R, SAS or other tools appropriate for large scale data preparation and analysis
  • Experience with data mining, machine learning, statistical modeling tools and underlying algorithms
  • Proficiency with Unix/Linux environments

Sound like a fit? We can't wait to hear from you.

Benefits

  • 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 (Boston) or Retirement Savings Plan (Montreal).
  • Easy commute with a paid-for public transportation or parking pass.
  • IATA Travel Agent Card for discounts in the travel industry.
  • Fully stocked kitchen with: coffee/tea, beer, bagels and snacks (both healthy and not-healthy).
  • Team lunches, off-site activities and much more!
  • In Cambridge, work in a historic factory building near Kendall Square; in Montreal, work in an artists loft in the Mile End.
Category: Data Science / Machine Learning
Full-time

See What It's Like To Work Here

Hopper is the award-winning mobile app that doesn't just let you book flights and hotels from your phone - it also tells you when is the best time to buy. No spam. No ads. No popups. No time wasted. Just the confidence that you're booking smart and saving money.

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