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 RoleWe 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 ResponsibilitiesDesign, 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 methodsImplement and tune boosting algorithms (XGBoost, LightGBM, CatBoost) and decision tree‑based models for classification and regression tasksPerform end‑to‑end data exploration, feature engineering, and model evaluationCollaborate with engineering teams to deploy models into production on Azure and DatabricksTranslate business problems into analytical frameworks and communicate results to technical and non‑technical audiencesStay current with emerging trends and tools in machine learning and data scienceProfile RequirementsEducationBachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Statistics, or a related quantitative fieldExperience & SkillsProven experience in recommender systems and time series forecastingStrong expertise in boosting algorithms (XGBoost, etc.) and decision treesProficiency in Python and key libraries: scikit-learn, pandas, NumPy, statsmodelsExperience with Azure Machine Learning, Databricks, and cloud-based model deploymentFamiliarity with C++ (a plus for performance‑critical components)Solid understanding of ML lifecycle, from prototyping to productionExcellent problem‑solving skills and ability to work independently in a fast‑paced environmentFluent in English (written and spoken) – essential for global collaborationWhy Join Us?Be part of a high-performing analytics team driving real business impactWork on cutting‑edge machine learning applications in a dynamic commercial environmentAccess to modern tools and cloud infrastructure (Azure, Databricks)Opportunities for growth within the Mantu Group ecosystem
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