Data Scientist

About the project

Project implemented for a client operating in the e-commerce sector.

Our expectations

• Minimum 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

Key tasks

• 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