Qualification & Experience:
• at least
• Good knowledge of Python (or R). Advanced Excel is helpful as well
• Practical experience developing sophisticated statistical or econometric models is a must
• Knowledge of classical algorithms and data structures (Linear/Logistic/Hierarchical regressions, Factor/Cluster analysis, Decision Tree-based algorithms, Time-series forecasting)
• Intermediate or higher English is a must
As a plus:
• Experience in advance ML (Gradient Boosting algorithms, Neural Networks) would be a plus
• Hands-on experience of working in Consumer goods domain: pricing and promotion analytics, marketing analytics, trade promotions, supply chain management, segmentation would be a plus
• Experience leading and working independently on end-to-end projects in a fast-paced environment is strongly preferred
• Best team: a multicultural team of bright specialists and friendly, helping people;
• Challenge: plenty of complex and exciting projects from international clients;
• Income: competitive salary and end-year bonuses;
• Vacation: paid leave of 27 business days per year;
• No micromanagement: we encourage self-organization and trust
• Learning and professional development: access to company learning platforms with free courses, external certifications and learning programs, free English classes;
• Being healthy: free health insurance;
• Communication: company parties, celebrations, workshops in different locations, cross-locations and cross-projects exchange programs.
• As a Data Scientist in our CPG practice, you will be building solutions that require analyzing client business problems and developing models to help solve them.
• Work in a fast-paced and dynamic environment; conducting research and prototyping innovations; data and requirements gathering; solution scoping and architecture.
• Execute quantitative data analyses that translates into actionable insights for the broader team.
• Be able to learn and pick up a new language/tool/ platform quickly.
• Collaborate and coordinate with different functional teams to implement models and monitor outcomes.
• Capable of working with development teams locally and globally.