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Data Engineer

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Summary

Data engineer/scientist role in Mumbai building demand and sales forecasting, inventory optimization, and computer-vision models (fabric defect detection, garment grading) for textile/apparel operations, then deploying them across departments. Stack includes Python, SQL, TensorFlow/PyTorch, BigQuery/Spark, SAP integration, and Power BI/Tableau.

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.


Skills

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See also

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