About the role
Project implemented for a client operating in the e-commerce sector.
Our expectations
- Minimum 3–5 years of experience in a Data Scientist role
- Experience in deploying machine learning models in a production environment
- Hands-on experience working with large datasets and large-scale models (BigQuery)
- Experience in integrating data from multiple sources and working with various data types: tabular, text (NLP), images, and time series
- Strong proficiency in Python and SQL
- Familiarity with Google Cloud Platform (GCP)
- Knowledge of Apache Airflow and Apache Spark
- Experience using Looker Studio for building reports and dashboards
- Strong understanding of statistical methods and machine learning algorithms
- Practical experience with tree-based algorithms (e.g., XGBoost, LightGBM, CatBoost)
- Ability to translate business challenges into machine learning problems
- Ability to independently define, test, and optimize ML models
- Willingness to propose your own solutions and approaches to data analysis
- Excellent communication skills – ability to explain complex technical topics to non-technical stakeholders
- Strong team player with a collaborative mindset and knowledge-sharing attitude
Main responsibilities
- Design, develop, and deploy machine learning models in production environments
- Analyze large, diverse datasets (tabular, text, images, time series)
- Integrate data from multiple internal and external sources to build robust data pipelines and features for ML models
- Conduct large-scale data analysis using tools such as BigQuery, ensuring scalability and performance
- Apply advanced statistical methods and machine learning algorithms
- Continuously improve and optimize existing models and data-driven solutions through testing and experimentation
- Work cross-functionally with business stakeholders, product managers, and UX teams to define ML use cases and align technical solutions with business goals
- Translate complex data and modeling outcomes into clear insights and recommendations for non-technical audiences
- Create and maintain dashboards and reports using Looker Studio to monitor model performance and data quality
- Propose new approaches, tools, or methodologies to enhance data science capabilities across the team
