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Description supplied by the original job listing.
Key Responsibilities
Build demand and sales forecasting models across divisions and seasons.
Optimize inventory and replenishment processes.
Plan production and detect anomalies in process data.
Implement computer vision for fabric defect detection and garment grading.
Develop real models using time series, classification, optimization, and vision techniques on messy, seasonal data.
Deploy models within various departments (planning, merchandising, supply chain, retail operations, finance, manufacturing, quality) by shadowing work processes, training staff, building champions, and writing SOPs.
Determine when to build versus buy analytics capabilities.
Manage APIs, integrate SAP with BigQuery, and handle data governance and reporting layers.
Requirements
8+ years of experience in data science, analytics, and technical delivery, with a focus on user-facing deployment.
Proficiency in forecasting techniques (ARIMA, Prophet, LSTM, XGBoost), regression, classification, clustering, and anomaly detection.
Experience in supply chain analytics and computer vision is a significant advantage.
Strong skills in Python, SQL, TensorFlow/PyTorch/Scikit-learn, Power BI or Tableau, and BigQuery or Spark.
Comfortable extracting data from SAP or any ERP.
Hands-on experience with applied AI on real problems, including prompting, retrieval, agents, and honest evaluation.
Evidence of teaching non-technical teams and ensuring sustained adoption of new workflows.
Preferred experience in textile, apparel, or garment industries; otherwise, manufacturing or physical operations.
Fluent in Hindi and English.
Work arrangement
No
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