At Proton, we're bringing cutting-edge machine learning to business-to-business distribution. By predicting what customers will buy, we're improving sales and efficiency, and driving growth. We're looking for a data scientist to help us make that vision a reality by developing and refining cutting-edge machine learning models and data processing systems.
Our outside sales product helps outside sales users — salespeople who visit the customers they sell to — do their jobs more effectively. You'll help build predictive models and use data to give them insights into their customers and across their sales portfolios. Our outside sales product, for example, uses machine learning for free-text product search using custom language models.
We are not looking to build a series of basic linear regressions with SciKit learn. Our data science group works with cutting-edge neural network architectures and other high-power machine learning techniques to solve deep problems with elegant solutions for our users. We believe deep solutions to big problems help solve the real problems our users face in their work.
This position reports to the lead engineer on the outside sales team. The data science group also regularly meets across teams (including our CTO). We have a journal club that meets regularly to discuss interesting ideas, we push to explore cutting-edge research, and we encourage collaboration across teams. You'll also have a chance to regularly speak with users to gain domain knowledge and tailor your ideas.
Our machine learning work mostly happens in Python using TensorFlow and Keras. Our infrastructure team works with the data science group on tooling for model training, testing, and deployment. We have a microservice architecture that makes working with data easy and secure. Familiarity with some programming and machine learning techniques is essential, but familiarity with these specific toolsets is not.
This role is for immediate start. Applications will be reviewed on a rolling basis. We're a remote-first company and open to candidates anywhere in the world.