A top-notch data-driven company. We’re growing so fast (180M users) that we’re collecting more data than we can monetize. Our Data Science group consists of ~50 people, of which there are 20+ data scientists, and others (engineering, curation and labeling) that help us make our projects successful and impactful for Wix. We apply SOTA Machine Learning techniques to Wix’s data to improve the product, internal processes and personalization for users, which in turn improves our profitability.
We’re looking for a Data Science Team Leader who is passionate about data science and analytical problem-solving to join our Kyiv office.
An extremely talented data scientist with at least 5 years’ experience with data science, machine learning, and/or deep learning and at least 2 years’ experience managing a successful team of data scientists. You have a deep understanding of classical ML & DL algs for a wide spectrum of problems and domains: Computer Vision, NLP, Recommendation Systems, Supervised & Unsupervised Learning.
You have the technical know-how to advise team members, the managerial skills to prioritize and advance projects and the interpersonal skills to communicate data science to non-technical management. You also have hands-on machine learning experience with Python. You’re willing to work hands-on, potentially working on your own project while managing the team.
Have an M.Sc or PhD in Math, Statistics, Computer Science, Physics, or an equivalent field.
Are familiar with Deep Learning frameworks and applications
Get to work on extremely diverse problems and domains.
Manage and mentor a team of talented data scientists with experience in various machine learning applications.
Serve as the technical expert of the team, providing high level guidance on all projects.
Direct and define projects based on the business requirements of various product managers.
Conduct advanced analysis, then design and code appropriate solutions using machine-learning, and communicating with all business partners.
Be responsible for building relationships with stakeholders in other business units, to identify aspects of the business/product that can benefit from data science and machine learning.