Data Analyst Specialist

Development and implementation of ML models (upcoming project: time series forecasting). Exploratory Data Analysis (EDA). Experiments with various approaches and model algorithms. Generation and testing of hypotheses to increase model quality. Management and prioritization of the hypothesis backlog. Development of infrastructure for tracking experiments, automatic data updates, and model retraining. Implementation (jointly with IT) of model result integrations into target systems. Visualization and interpretation of results for business units. Maintaining documentation. Participation in the development of internal ML tools and team best practices

Requirements

Data Scientist work experience from 2 years; Experience in a team development format with a shared codebase in Gitlab; Proficient in Python and key libraries for data analysis, machine learning, and visualization: PySpark, pandas, NumPy, scikit-learn, plotly; Practical experience in model development and result interpretation based on gradient boosting: LightGBM, CatBoost, or XGBoost; Understanding of time series forecasting specifics: lag features, rolling statistics, seasonality, time-based validation; Proficient knowledge of SQL; Experience working with DWH and object storage (S3); Understanding of ML model principles in production. Familiarity with MLOps practices; Experience working with Airflow, Docker, and CI/CD. English language at the level of reading technical documentation

Higher education — Bachelor's degree; Experience: 2 years