Senior Data Scientist

Marketing Data & Analytics New York, United States


Description

The role:

Currently a team of 4 in our New York office, we’re looking to grow to up to 10 people and build our first Tech Hub in the United States. This is a really exciting time to join the business, with our recent acquisition of Stadium Goods and our IPO back in 2018, you’ll have the chance to be a part of a brand new function and work exclusively on large scale, high-impact projects.

All of our work in Data Science is directed at building software solutions that enhance the marketing activity of the company by using Machine Learning and advanced statistical methods. This means understanding the customer, figuring out who they are, what they want and how to get their attention. Critically, we build systems that do this autonomously.

What you'll do:

  • Work with large, complex datasets, solve hard problems using advanced statistical and Machine Learning techniques.
  • Prototype and productionize Machine Learning pipelines to provide a solution to large commercial impact problems, particularly in the Digital Marketing space that keep Farfetch ahead of the competition.
  • Collaborate with other Scientists and Engineers to build efficient data products. Identify opportunities for, design, and assess improvements to Farfetch products.
  • Research and develop forecasting and optimization methods to improve the quality of Farfetch's Digital Marketing activity; including paid search, behavioral modeling, and live experiments.

Who you are:

  • At least 4 year experience in an advanced Engineering and Data Science role, preferably in the adtech space.
  • Extensive experience building Machine Learning and Deep Learning models on large datasets.
  • Fluent in Python or alternative object-orientated programming languages. Experience developing production software is a bonus.
  • Ideally, an MS degree holder in a quantitative discipline (e.g., computer science, economics, mathematics, statistics, physics, electrical engineering, industrial engineering).
  • Experience in Bayesian Inference and Reinforcement Learning is a bonus.