- 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 :

1. MSc in Statistics & Operations Research

2. M.Tech. in Industrial Engineering

3. Applied Mathematics / Statistics

4. Computer Science

5. MBA in Operations

- Certifications in one or more of the following areas will be an added advantage :

1. Python

2. AI/ML

3. Optimization

4. Simulation

5. 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 :

1. Data manipulation

2. Data visualization

3. 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.