We are looking for a Data Scientist with expertise in classical machine learning and predictive analytics to build custom models for equipment manufacturing and industrial environments. You will analyze sensor, time-series, and operational data to solve critical challenges, including predictive maintenance, equipment failure prediction, quality forecasting, and process optimization.
Key Responsibilities
Model Development: Design, train, validate, and deploy end-to-end classical ML and time-series models using Python.
Feature Engineering & Analytics: Clean and transform structured, sensor, and time-series data from SCADA, PLC, MES, and ERP systems into actionable features.
Problem Solving: Evaluate and optimize algorithms based on business objectives, metrics, and interpretability
requirements
. • Cross-Functional Collaboration: Partner with manufacturing, process engineering, QA, and maintenance teams to translate operational bottlenecks into ML solutions. • Deployment & Monitoring: Deploy production-ready models into operational workflows and continuously monitor performance and reliability. Technical Stack &