OUTFITTERY is Europe’s largest Personal Shopping Service for men. We know that shopping isn’t a pleasure for every man, but we’re here to change that! This is why we set a clear goal: a world where men have time for the important things in life and are still well-dressed.
Are you looking for an amazing playground, where you can apply your machine learning skills? Do you want to take over responsibility in building up a data driven company? Then become part of our Data Department as Research Lead Machine Learning (m/f)!
The Data Science team works at the intersection of statistics, machine learning and engineering to tackle some of the most challenging and interesting problems, ranging from deep learning, multi-modal feature representation to working with unstructured text data. Our goal is to create an AI that is as knowledgeable about fashion as a human stylist.
Moreover, the team plays a decisive role part in the company’s strategy to become data driven.
The ideal candidate has a strong background in machine learning research, but is passionate about solving real-world problems. We are looking for someone who believes in implementing and testing ideas rather than talking about them; someone who loves building data products and models.
In this role, you will closely collaborate with colleagues within the data science team to conceptualize, implement and evaluate state-of-the-art algorithmic solutions. To this end, you will mentor other data scientists, serve as the local expert in all aspects of machine learning. You will be likewise responsible of leading exploratory research initiatives and of supervising the transfer into a final product. This is an opportunity to work in a highly impactful, visible role that will be transformative to Outfittery. The ideal candidate should be equally comfortable developing mathematical models, writing code, choosing appropriate statistical methods, mentoring other data scientists and being accountable for the success of research projects.
Intrigued? Then send us your application with your salary expectations and possible starting date. Your contact person is Elise Hart.