Data Scientist

Job Summary

Analyze manufacturing plant and process data to deliver data-driven solutions that optimize operations. Develop and deploy machine learning models using Seeq and Python, collaborating with cross-functional teams to improve predictive maintenance, process efficiency, and quality outcomes.

Responsibilities

• Analyze manufacturing plant and process data to identify patterns, anomalies, and optimization opportunities
• Perform time-series analysis, root cause investigation, and process monitoring using the Seeq platform (Workbench and Data Lab)
• Develop and deploy machine learning models for predictive maintenance, process efficiency improvement, and quality/yield optimization
• Collaborate with plant, engineering, and operations teams to translate business challenges into data science solutions
• Build and maintain data pipelines, analytical datasets, and workflows to support operational analytics
• Monitor, evaluate, and continuously improve model performance in production environments
• Present actionable insights through dashboards, reports, and stakeholder discussions to drive informed decision-making
• Ensure data quality, reliability, and governance across manufacturing data sources
• Promote adoption of data-driven decision-making across plant operations

Preferred competencies and qualifications

• Experience in industries such as Oil & Gas, Chemicals, and Manufacturing
• Knowledge of MLOps including model deployment, monitoring, and pipeline management
• Exposure to optimization techniques for industrial processes
• Familiarity with cloud platforms such as Azure, AWS, or GCP
• Experience with data visualization tools, real-time/streaming data analytics, and data engineering (ETL, data pipelines, data lakes)