Position: Middle Data Scientist
Company: Fozzy group
Category: Data Science
Experience required: 2y
English level: intermediate

Job Responsibilities

Interpreting and translating business problems into analytical solutions for optimization and development of Workforce Planning model;
Involvement in the entire project life cycle including data extraction, data cleaning, statistical modeling, and data visualization with large data sets of structured and unstructured data.
Creating algorithms models to identify drivers of growth, losses and profitability for initiatives to support business decisions;
Designing the system data flow to DWH with support of Data Architects;
Analytical support for project initiative effects estimation creation of decision support reports;
Communication with key stakeholders (HR, Finance, Operational Commercial Departments) to design implement Workforce Planning initiatives;
Keeping close contact with regional management and Continuous Transformation team.
Requirements

Bachelor's Degree in Mathematics / Quantitative Economics / Econometrics / Statistics / Computer Sciences / Finance;
At least 1 year working experience on Data Analytics;
Strong mathematical background in Linear algebra, Probability, Statistics Optimization Techniques;
Experience in handling Structured and Unstructured data, writing advanced SQL queries, Data Wrangling, Data Visualization, Data Acquisition Predictive modeling;
Willingness to learn, professionalism and dedication, able to work under pressure;
Skills

Must Have

Python (at least numpy, pandas, sklearn, pulp);
SQL (Window Analytic functions, Nested Queries);
Advanced Excel (Pivot Tables VBA);
Skills in Advanced Regression Modeling, Probabilistic Graphical Models, Multivariate Analysis, Time Series Analysis and application of Statistical Concepts (Hypothesis testing, A/B tests, Factor analysis / PCA).
Preferred

Experience of modelling non-continuous events, implementation of Linear Optimization Methods (Mixed-Integer Linear Programming);
Knowledge of Reporting and Business Intelligence Software (Power BI, Tableau, Qlik, Cognos Analytics);
Machine Learning techniques (Decision Trees, Random Forest, SVM, Bayesian, XG Boost, K-Nearest Neighbors).
What We Offer