As the lead of one of our data science teams, you will be directly responsible for delivering intelligent features to our users. You will lead a team of data scientists and machine learning engineers to ideate, build and serve the models that fuel Miro’s intelligence, working in close contact with Product, Design and Engineering. You will hire and coach the best talent and provide technical direction to deliver solutions that delight our 25M users. Most importantly, as you’ll be doing all this as a senior member of the wonderful Data Science crew at Miro, playing a key role in shaping the strategy of the department and the future of Machine learning at Miro!
Each role at Miro is based at one of our physical hubs and we look for talent that want to be part of these local, collaborative communities. Mironeers work in a hybrid model, with a 3 days a week in office culture as our baseline.
About The Team
The Data Science team at Miro has a mission: make Miro so intelligent that users will start considering it a team member, rather than a collaboration platform. We work with NLP, Computer Vision, Graphs and Multimodal deep learning to give Miro the means to truly understand what its users want and need to do, and support them in the process of creating the next big thing. We are an international and interdisciplinary team, which values diversity in background and culture and is excited to learn something new every day from its multi-faceted members.
What You’ll Do
Build and scale the Data Science product team, embedding and growing the talent it needs
Deeply understand the needs of our customers and partner with product and design to shape Miro’s intelligent features
Provide technical and thought leadership to data scientists
Orchestrate end-to-end intelligent feature delivery, including model deployment in production
Contribute to craft the strategy of the Data Science department of Miro
What You’ll Need
2+ yrs (formal or informal) experience as Data Science Leader
Deep understanding of Machine Learning algorithms: Artificial Neural Networks/Deep Learning, Ensemble methods, Unsupervised learning methods, time series forecasting
A proven understanding of Machine Learning Engineering and of what it takes to productize models at scale in SaaS products
A specialization in either Search/Recommendation, NLP or Computer Vision is a plus
Empathy, with customers, colleagues and team members
Ability to switch between long term thinking and short term pragmatism
Level of experience (years):
Mid Career (2+ years of experience)