Data Scientist Offline

Responsibilities:

• 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.

 

Project description

- provide accurate mid-term forecast (1.5 years) for sales for a big international client in CPG industry

- identify leading drivers for growth and contribution (drivers decomposition)

- tools - python, pyspark on Azure data bricks

 

Qualification & Experience:

• ~2 years of relevant work experience running data analytics projects

• Practical experience developing sophisticated statistical or econometric models is a must

• Goof knowledge of Python.

• 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)

 

We offer:

• 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, English classes with the opportunity to upgrade your grammar and speaking skills;

• Being healthy: free health insurance;

• Communication: company parties, celebrations, workshops in different locations, cross-locations and cross-projects exchange programs.