Big-Data Platform and Data Engineer / Data Scientist
Easysize Copenhagen €50k – €65k Long term Any
About Easysize

Easysize helps online fashion retailers and brands to reduce returns using data driven approach. Large database and machine learning help us to predict the right clothing size and identify possible returns.

Job Description

Easysize is looking for an experienced Big Data Platform and Data Engineer / Data Scientist to join our team in Copenhagen.

We are growing and are looking for a person to lead our effort to level-up our infrastructure and data processes to handle ever-larger data volumes and prediction requests.

You’ll be working on improving real time delivery of predictions, our existing algorithms, experimenting and improving data structures, helping to build new analytical tools and dashboards for fashion retailers. Our data comes from various retailers and third-party services all around the world. We ship product improvements on a daily basis, and constantly work on optimising accuracy, performance and speed of the size prediction. The ideal candidate for this role will help in increasing the volume of data we can ingest and the speed with which our API returns predictions to our customers.

You will get to: 

  • Work with fashion data on millions users. 
  • Work on performance and accuracy of our algorithms. 
  • Take part in product development and company life.

You might be the right fit, if: 

  • You’re able to take a responsibility and a lead in “big data” vertical in the company and grow, as the company evolves. 
  • You are a team player. 
  • You are product oriented: Great code is only great if it solves real problems for the customer.
  • You enjoy moving fast.


Your Skills / Experience: 

  • Experience with big data (Spark, Hadoop, Kafka, etc.). You will lead our effort to migrate technologies to support our scale. You will also work on supporting these technologies after they are set up. 
  • Practical knowledge in analysis on large sets of categorical data (statistical modelling, predictive analysis, probabilistic modelling, supervised learning). 
  • Python and general programming skills.
  • Passion for algorithms, data and problem solving.

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