Data Scientist

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