Data Scientist, Product Finance

United States

Applications have closed

Hopper

Score unbelievable travel deals exclusively in the Hopper App

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Minimum qualifications• 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 conducting empirical research and answering hard questions with data• A self starter mentality and the ability to thrive in uncertainty• Experience with relational databases and SQL• Experience in Pandas, R, SAS or other tools appropriate for large scale data preparation and analysis• Experience with machine learning, statistical modeling tools and underlying algorithms• Experience with business reporting tools such as Tableau, Amplitude• Proficiency with Unix/Linux environments
About the jobWe’re looking for a passionate and motivated data scientist to help us capitalize on key data-centric opportunities within finance. You’ll be at the intersection between finance and data in a product led organisation - discovering and executing on opportunities within our payments solutions, supporting decision making across a wide range of business areas, and driving automation and process improvement. You will have a visible and direct impact on our bottom line and on our business as a whole.  Specific challenges include developing and deploying fraud protection models at scale; building statistical models to extrapolate current and historical trends into forward looking forecasts; and creating efficient tools for interactions with third party payment providers and financial institutions.

Responsibilities

  • Frame and conduct complex exploratory analyses needed to deepen our understanding of Hopper users and how they transact
  • Directly build product improvements and initiatives, design data pipelines, and create a risk strategy framework
  • Use machine learning and big data tools on large and complex data sets to create risk models
  • Create advanced dashboards for product experiment tracking and business unit performance analysis using Amplitude, Tableau and BigQuery/Google sheets
  • Find effective ways to simplify and communicate analyses to a non-technical audience

Benefits

  • Well-funded and proven startup with large ambitions, competitive salary and stock options
  • Unlimited PTO
  • WeWork All Access Pass OR Work-from-home stipend
  • Entrepreneurial culture where pushing limits and taking risks is everyday business
  • Open communication with management and company leadership
  • Small, dynamic teams = massive impact
  • 100% employer paid medical, dental, vision, disability and life insurance plans
  • Access to a 401k 
More about HopperToday, Hopper is best known as a travel app. We're going to do about $1B in sales this year and weathered the COVID storm better than anyone expected. We just raised $170M from Goldman Sachs and Capital One, and inked a deal to be the exclusive travel provider for Capital One Travel.
We owe our success, in large part, to a proprietary suite of data-driven and risk-based financial services that we have developed that complement a customer's trip-purchasing experience. One example is Price Freeze, where our customers are able to purchase a financial option in the app to lock in any price that they see, on any item, for as short as 1 hour or as long as 21 days with Hopper taking the risk on the other side of the trade.
Now we're laying the groundwork for continued expansion in 2021 by adding great people to our team who can help us compete with the travel giants.
#LI-Remote#BI-Remote

Tags: Amplitude Big Data BigQuery Computer Science Data pipelines Engineering Finance Linux Machine Learning Pandas Pipelines R RDBMS Research SAS SQL Statistical modeling Statistics Tableau

Perks/benefits: Career development Competitive pay Equity Health care Home office stipend Insurance Startup environment Travel Unlimited paid time off

Region: North America
Country: United States
Job stats:  15  5  0
Category: Data Science Jobs

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