Generate insights into customer behavior and derive modeling ideas for improving our content recommender system
Work with data engineers to define what additional customer data we might want to collect and help make it available in a format suitable for modeling purposes
Create meaningful machine-learning features that improve our content recommender’s performance measured through offline metrics and online a/b tests
Build machine learning models and deploy them as part of our recommender system
Requirements & Skills:
Master’s degree or equivalent experience (2+ years) in a relevant field or industry
Solid understanding of machine learning fundamentals
High comfort level in Python or other programming language
Familiarity with an ML stack such as typical scientific Python libraries (pandas, numpy, sklearn, xgboost) or deep learning frameworks (we use Pytorch)
Familiarity with data analysis through SQL or a big-data processing framework such as Spark
Ability to collaborate with technical partners – you’ll be working closely with other teams to determine requirements for your work and to make design decisions that affect our stack
The idea of writing and deploying production code, and getting real-world feedback on your models excites you
A desire to always be learning and contributing to a collaborative environment
