We are looking for a Data Scientist who can work on real-world manufacturing and business problems using machine learning, statistics, and data engineering principles.
The role is not limited to building models. You will work closely with product, engineering, and manufacturing domain teams to convert industrial data into actionable intelligence.
You will contribute to:
- Forecasting production and demand
- Predictive maintenance
- Anomaly detection
- Optimization and recommendation systems
- KPI intelligence and root-cause analysis
- AI-driven decision support systems
This is a hands-on role suited for someone who enjoys solving practical industrial problems rather than working only on academic datasets.
Key Responsibilities
Data Understanding & Preparation
- Analyze structured and semi-structured industrial datasets
- Clean, preprocess, and transform ERP, MES, IoT, and machine data
- Perform feature engineering for time-series and operational datasets
- Build reusable data pipelines for ML workflows
Machine Learning & Analytics
- Develop predictive and prescriptive ML models
- Work on:
- Time-series forecasting
- Classification and regression
- Anomaly detection
- Optimization models
- Evaluate model performance and improve accuracy continuously
- Build explainable AI outputs for business users
Business Problem Solving
- Translate manufacturing problems into analytical models
- Identify operational bottlenecks and performance drivers
- Work on OEE, downtime, scrap, throughput, energy, and supply chain analytics
- Support ROI-oriented decision intelligence
Collaboration
- Work with backend engineers, frontend teams, and product stakeholders
- Collaborate with manufacturing experts to validate model outputs
- Participate in architecture and solution discussions
Deployment & Monitoring
- Support deployment of ML models into production systems
- Monitor model drift and performance degradation
- Contribute to MLOps and model lifecycle management
Required Skil
📌 Data Scientist (Chennai)
🏢 Plantnxt Technologies
📍 Chennai
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