Description
Our Data Science team focuses on modelling complex business problems and deploying data products at scale. Our work spans across multiple areas including physical stores, online, supply chain, marketing, where we encourage rotation amongst our Data Scientists so they can gain expertise in different subjects.
We work on several domains and problem types: online, pricing, security, fulfilment, distribution, property, IoT and computer vision are just some.
We have a team of engineers who help productionise data science products, building scalable and robust solutions.
Our team members spend 10% of their week on learning and personal development. Multiple academic collaborations enrich the team expertise; knowledge sharing events are regular. Furthermore, we have a great work-life balance, team days and a relaxed but engaging culture.
Role Description
This is a hands-on role where the engineer will be responsible for putting into production data science solutions, machine learning or other mathematical models. You will be able to work on the whole end to end pipeline of our data products, building ETL for modelling purposes, model training, monitoring and alerting solutions.
Our engineers will need to be able to work on different environments, on premise and on the cloud, collaborate to improve our routines and recommend new ones.
We expect our engineers to research new technologies and propose new solutions in order to keep our tech stack up to date and relevant.
Tech stack
The candidate needs to be fluent in Python.
Experience with other languages is a plus (in particular Java, other JVM languages, or C/C++).
Some knowledge of (py)Spark and Hadoop stack is recommended.
Additionally, we positively evaluate familiarity with creating APIs and micro-services, experience with cloud solutions (Azure in particular), as well as some proficiency in Linux environment and knowledge of DevOps solutions.