Data Scientist

Key Responsibilities

• Analyze manufacturing processes, energy consumption patterns, and operational constraints to identify optimization opportunities.
• Develop and enhance predictive, prescriptive, and optimization models focused on reducing energy consumption and improving operational efficiency.
• Leverage PI Historian (AVEVA PI System) and other manufacturing data sources to generate actionable insights and recommendations.
• Define modeling strategies based on business objectives, process understanding, and site-specific operating conditions.
• Build analytical frameworks that can be replicated and adapted across different manufacturing facilities.
• Partner with business stakeholders, process engineers, and operations teams to drive adoption and value realization.
• Conduct root cause analysis and identify key operating parameters influencing energy performance.
• Monitor model performance and continuously improve solution accuracy, scalability, and business impact.
• Communicate complex analytical findings to both technical and non-technical stakeholders.

Required Qualifications

• 10+ years of experience in Data Science, Advanced Analytics, or AI within manufacturing environments.
• Proven experience working with PI Historian (OSIsoft/AVEVA PI System) and industrial time-series data.
• Strong experience developing optimization models for manufacturing operations, with a focus on energy efficiency and sustainability use cases.
• Demonstrated ability to understand business problems and translate them into effective analytical and modeling solutions.
• Experience working directly with manufacturing operations, process engineers, and business stakeholders.

Technical Skills

• Machine Learning and Advanced Analytics, Statistical Modeling and Predictive Analytics, Optimization Techniques and Prescriptive Analytics
• Python, SQL, Databricks and Azure
• Industrial Data Analytics and Process Monitoring
• Root Cause Analysis and Process Optimization

Preferred Experience

• Exposure to sustainability, decarbonization, and energy management initiatives will be added advantage.
• Experience working within cross-functional business, engineering, and analytics teams.