DESCRIPTION
Hopper is a new kind of travel company that uses big data to empower travelers. The Hopper app for iOS and Android analyses trillions of past and current trips to predict when you should fly and buy. The app notifies you when fares drop so you can book flights at just the right moment. Hopper is among the fastest growing travel apps ever, with over 10 million installs since it was launched in 2015.
But this is just the beginning. Learn more.
We’re looking for a data-savvy individual to join our team as a data scientist, to create consumer-focused research content and support user-centric product development and growth 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.
We're looking for someone to fill this role in a full-time capacity immediately, so unfortunately we are unable to consider 2016 degree candidates at this time.
In this role you will
- Transform complex analyses into short, compelling, and easy to understand studies to share with journalists aimed at a consumer audience
- Frame and conduct complex analyses and experiments using tremendously large (e.g. 10^6 to 10^10 records), complex (not always well-structured, highly variable) data sets
- Design and implement ad hoc and automated analysis scripts, design and deliver appropriate summary tables, charts and interactive tools to present your results
REQUIREMENTS
A qualified candidate has
- A degree in Math, Statistics, Computer Science, Engineering or other quantitative discipline
- 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
Compensation will be competitive including equity in an early stage startup backed by top-tier VCs (Atlas Venture, Brightspark and OMERS Ventures).
All your information will be kept confidential according to EEO guidelines.