Data Scientist - Machine Learning

Job Description :

Experience & Education :

• 2 - 3 years of relevant experience in Machine Learning, Time Series Forecasting, Optimization Techniques, or related areas.
• Master's degree in Technology, Engineering, or a quantitative discipline such as :
• MSc in Statistics & Operations Research
• M.Tech. in Industrial Engineering
• Applied Mathematics / Statistics
• Computer Science
• MBA in Operations
• Certifications in one or more of the following areas will be an added advantage :
• Python
• AI/ML
• Optimization
• Simulation
• Cloud Platforms - Azure / GCP / AWS

Mandatory Skills :

• Strong proficiency in data modelling, preferably developed through client-facing projects.
• Extensive experience applying data-driven techniques such as Exploratory Data Analysis (EDA) and data preprocessing to solve business problems.
• Strong hands-on experience with Python/PySpark for :
• Data manipulation
• Data visualization
• Machine Learning model development
• Proficiency in at least one cloud platform: Azure, GCP, or AWS.
• Strong SQL skills for data preparation, manipulation, and descriptive analysis.
• Strong understanding and hands-on experience in the Supply Chain domain.
• Excellent written and verbal communication skills.

Good-to-Have Skills :

• Experience with Simulation and Optimization techniques.
• Experience with visualization tools such as Tableau or Power BI.
• Exposure to supply chain planning platforms such as BY, Anaplan, o9, Kinaxis, or SAP IBP.
• Exposure to client interaction and stakeholder management.
• Experience working with business planning platforms such as o9, Kinaxis, or Blue Yonder (BY).
• Exposure to supply chain analytics, forecasting, planning, and optimisation use cases.

Key Responsibilities :

• Apply Machine Learning, forecasting, optimization, and data-driven techniques to solve complex supply chain business problems.
• Perform data exploration, preprocessing, modelling, and analysis using Python, PySpark, and SQL.
• Develop and implement machine learning and time-series forecasting models.
• Analyse supply chain datasets and translate business requirements into analytical solutions.
• Leverage cloud platforms to develop and deploy scalable analytics solutions.
• Work with optimization and simulation techniques to improve supply chain planning and decision-making.
• Develop meaningful data visualizations and analytical insights for business stakeholders.
• Collaborate with cross-functional and client teams to understand requirements and deliver data-driven solutions.
• Support implementation and integration of analytics solutions with supply chain planning platforms.