- Experience
- 8+ yrs
- Salary
- —
- Openings
- 1
- Posted
- 6 days ago
- Work mode
- In office
- Resume
- Required to apply
Where you'll work
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Job description
Key Responsibilities
- Develop demand and sales forecasting models tailored to various divisions and seasonal patterns.
- Enhance inventory management and replenishment workflows to increase efficiency.
- Oversee production planning while identifying anomalies in process data to ensure quality.
- Apply computer vision techniques for detecting fabric defects and grading garments.
- Create practical models utilizing time series analysis, classification, optimization, and computer vision on complex, seasonal datasets.
- Implement and deploy models across departments including planning, merchandising, supply chain, retail operations, finance, manufacturing, and quality assurance by closely observing workflows, educating personnel, cultivating internal advocates, and documenting standard operating procedures.
- Assess and decide between building in-house analytics solutions or procuring external tools.
- Manage API integrations, synchronize SAP systems with BigQuery, and oversee data governance and reporting structures.
Qualifications and Experience
- Minimum of eight years in data science, analytics, and technical project execution, emphasizing user-facing model deployment.
- Expertise in forecasting methods such as ARIMA, Prophet, LSTM, and XGBoost, alongside regression, classification, clustering, and anomaly detection techniques.
- Substantial experience in supply chain analytics and computer vision technologies is highly desirable.
- Proficiency in Python programming, SQL, machine learning frameworks including TensorFlow, PyTorch, or Scikit-learn, visualization tools such as Power BI or Tableau, and big data platforms like BigQuery or Spark.
- Skilled in extracting and managing data from SAP or equivalent ERP systems.
- Hands-on knowledge of applied artificial intelligence addressing real-world challenges, including techniques like prompting, retrieval, agents, and conducting honest evaluations.
- Demonstrated ability to train non-technical teams and promote long-term adoption of innovative workflows.
- Experience in the textile, apparel, or garment manufacturing sector is a plus; alternatively, experience in manufacturing or physical operational domains is acceptable.
- Fluency in both Hindi and English languages.