Senior Data Scientist

Job Summary

We are looking for a Senior Data Scientist with strong expertise in Machine Learning, predictive analytics, and industrial data science to drive smart manufacturing and Industry 4.0 initiatives. The candidate will develop data-driven solutions to improve equipment reliability, manufacturing efficiency, product quality, and operational performance.

Key Responsibilities

• Design, develop, and deploy machine learning models for predictive maintenance, anomaly detection, and manufacturing process optimization.

• Analyze large-scale manufacturing, sensor, and Industrial IoT datasets to identify patterns and actionable insights.

• Build predictive models for equipment failures, production performance, energy consumption, and quality monitoring.

• Apply statistical modeling, feature engineering, regression, classification, ensemble methods, and time-series forecasting.

• Develop scalable data processing pipelines using Python, SQL, and PySpark.

• Collaborate with manufacturing, engineering, and digital transformation teams to solve real-world industrial challenges.

• Support model deployment, performance monitoring, and continuous improvement of ML solutions.

• Measure business impact through reduced downtime, improved Overall Equipment Effectiveness (OEE), enhanced quality, and optimized resource utilization.

Mandatory Skills

• Strong hands-on programming experience in Python and SQL.

• Expertise in Machine Learning, statistical modeling, and predictive analytics.

• Experience with predictive maintenance, anomaly detection, or time-series forecasting.

• Knowledge of feature engineering, model validation, and performance optimization.

• Experience processing large datasets; PySpark or Apache Spark is preferred.

• Practical exposure to manufacturing analytics, Industry 4.0, Industrial IoT, or smart factory environments.

Preferred Skills

• Sensor data analytics, condition monitoring, and equipment performance modeling.

• OEE, production scheduling, energy optimization, and quality analytics.

• Industrial data integration and familiarity with IoT data protocols such as MQTT or OPC UA.

• Experience deploying ML models into production environments on AWS or Azure.