Data Scientist - Experimentation

Recruiter
Farfetch
Location
Porto, PT
Posted
24 Jun 2020
Closes
07 Aug 2020
Ref
252a5359-a143-48fd-a498-3b901cd7ff20
Level
Manager
The Role

We're looking for someone who wants to be part of our world-leading experimentation culture at Farfetch and evolve our internal experimentation Platform.

We know that our ability to make scientifically-informed, rapid iterations is key to our success, and we're looking for a Data Scientist to accelerate our automation.

You will be working in a very friendly environment and be part of a well-motivated, multicultural, talented and growing team of Software Engineers, QAs, Data Scientists and Data Analysts, to help build and optimize our data-driven products in a big data context.

What you'll do

  • Design and develop state of the art statistical methodologies for experimentation;
  • Conduct practical research with a scientific mindset, and a focus on delivery;
  • Build large scale data pipelines;
  • Work closely with engineers to put code in production;
  • Engage with analytics team, business stakeholders, product managers to help deliver a shared vision of a experimentation platform;
  • Scientific and technical publications are possible and encouraged.


Who you are

  • MSc in a quantitative discipline: Machine Learning, Computer Science, Statistics, Applied Mathematics, Physics or related areas;
  • Strong statistical knowledge (hypothesis testing, causal inference, regressions);
  • Experience designing and analysing A/B tests is highly valued;
  • Fluent in Python and common numerical packages (NumPy, SciPy, Scikit-Learn, Pandas). Experience developing production software is a bonus;
  • Experience dealing with large amounts of data and building data pipelines;
  • Strong English skills, both written and spoken;
  • Be interested to keep up to date with scientific advancements.

As a Data Scientist within our Experimentation team, you will work along with a team of Software Engineers, QAs, Data Scientists and Data Analysts to help build and optimize our data-driven products in a big data context.