Description :

We are seeking an accomplished Lead Data Science professional with 10-14 years of experience in designing, developing, and deploying advanced machine learning and AI solutions across supply chain, manufacturing, and operational domains. The ideal candidate will have a proven track record in building traditional ML models (demand forecasting, inventory optimization) and manufacturing-specific models (energy optimization, yield prediction, computer vision, video analytics) to drive measurable business impact.

Job Responsibilities :

Leadership & Strategy :

- Lead and mentor a team of data scientists and ML engineers.

- Define data science roadmap aligned with business priorities in supply chain and manufacturing.

- Collaborate with cross-functional teams to drive data-driven decision-making.

Supply Chain & Demand Forecasting :

- Build traditional ML models for :

a. Demand forecasting (time-series : ARIMA, Prophet, LSTM, XGBoost)

b. Inventory optimization and supply chain planning

c. Logistics and warehouse optimization

Manufacturing & Operational Models :

- Develop advanced analytics models for :

a. Energy optimization (predictive maintenance, consumption forecasting)

b. Throughput & yield optimization (production scheduling, quality prediction)

c. Predictive maintenance (failure prediction, anomaly detection)

e. Leverage IoT, SCADA, and sensor data for real-time insights.

Computer Vision & Video Analytics :

- Build computer vision solutions for :

a. Quality inspection and defect detection

b. Video analytics (safety monitoring, equipment tracking

c. Object detection and classification (YOLO, Faster R-CNN, ResNet)

d. Deploy edge AI solutions for real-time inference.

Model Deployment & MLOps :

- Implement end-to-end ML pipelines (data ingestion, feature engineering, deployment).

- Establish MLOps best practices (CI/CD, model monitoring, versioning).

- Ensure scalability and reliability of production models.

Stakeholder Engagement :

- Present insights and recommendations to senior leadership.

- Translate technical concepts into actionable business strategies.

REQUIRED EDUCATION AND EXPERIENCE :

- BE/B.Tech/M.Tech/MS in Data Science, Computer Science, Statistics, Operations Research, or related field.

- 10-14 years of hands-on experience in data science, machine learning, and analytics.

- Programming Languages : Python, R, SQL

- ML Frameworks : Scikit-learn, TensorFlow, PyTorch, Keras, XGBoost, LightGBM

- Computer Vision : OpenCV, YOLO, Faster R-CNN, Mask R-CNN, ResNet, EfficientNet

- Time-Series Forecasting : ARIMA, Prophet, LSTM, GRU, Transformer models

- Big Data & Cloud : Spark, Hadoop, Azure (ML Studio, Synapse)

- Experience in manufacturing industries (chemicals, automotive, FMCG, pharmaceuticals, or related).