Data scientist

Mission Description: Join our Advanced Analytics team as a Data Scientist in the Commercial Performance Tower.

You will play a key role in designing, developing, and deploying scalable machine learning models that drive business impact.

This is a hands-on role focused on model development, deployment, and optimization in real-world commercial environments.

About the Role: We are seeking a skilled and proactive Data Scientist to strengthen our analytics capabilities.

You will work on high-impact projects involving recommendation systems, demand forecasting, and predictive modeling using state-of-the-art techniques.

The ideal candidate is passionate about turning data into actionable insights and has strong experience in model deployment within cloud environments (Azure, Databricks).

You will collaborate closely with data engineers, ML engineers, and business stakeholders to deliver end-to-end data science solutions that optimize commercial performance.

Key Responsibilities: Design, develop, and optimize recommendation systems (collaborative filtering, content-based, hybrid approaches) Build and validate time series forecasting models using ARIMA, Prophet, LSTM, and other ML-based methods Implement and tune boosting algorithms (XGBoost, Light GBM, Cat Boost) and decision tree-based models for classification and regression tasks Perform end-to-end data exploration, feature engineering, and model evaluation Collaborate with engineering teams to deploy models into production on Azure and Databricks Translate business problems into analytical frameworks and communicate results to technical and non-technical audiences Stay current with emerging trends and tools in machine learning and data science Profile Requirements: Education: Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Statistics , or a related quantitative field Experience & Skills: Proven experience in recommender systems and time series forecasting Strong expertise in boosting algorithms (XGBoost, etc.) and decision trees Proficiency in Python and key libraries: scikit-learn, pandas, Num Py, statsmodels Experience with Azure Machine Learning , Databricks , and cloud-based model deployment Familiarity with C++ (a plus for performance-critical components) Solid understanding of ML lifecycle , from prototyping to production Excellent problem-solving skills and ability to work independently in a fast-paced environment Fluent in English (written and spoken) – essential for global collaboration Why Join Us? Be part of a high-performing analytics team driving real business impact Work on cutting-edge machine learning applications in a dynamic commercial environment Access to modern tools and cloud infrastructure (Azure, Databricks) Opportunities for growth within the Mantu Group ecosystem