Collaborate with fellow Data Scientists, Analysts and Engineers to drive innovation and develop top-notch analytical models and methods
Support and impact critical business decisions in areas of supply chain and marketing
responsibilities :
Actively participate in each stage of the data science lifecycle, from business understanding through model development to industrialization
Design, build and maintain statistical/machine learning models to optimize business operations
Explore and experiment with innovative ML techniques and approaches to maximize value generated by the team
Be a thought leader in development of methodology within big scale transformational projects
Communicate model & analysis results to a non-technical audience that includes stakeholders and senior management, and win their buy-in
Coach and mentor other team members on multiple aspects of a data scientist role
requirements-expected :
2+ years of professional experience building and industrializing machine learning solutions
Very good command of Python and its use with version control (git) and testing
Practical knowledge of SQL, PySpark & Databricks
Experience in application of ML concepts and methodologies (regression and classification, time series modeling, feature engineering and selection, regularization etc.)
Solid knowledge of ML techniques and algorithms (incl. various regression types, ensembles, clustering, decision trees, boosting, etc.) and their pros and cons
Ability to reframe business challenges into data science problems and adjust ML methods & tools accordingly
Good communication and presentation skills, in particular facilitation of grasping complex topics by broad audiences, incl. non-technical stakeholders
Track record of effective collaboration with IT / data engineering teams in development and production phase
