Data Scientist

Iyan Cloud Tamilnadu; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Iyan Cloud Tamilnadu is seeking a senior Data Scientist to optimize manufacturing energy use and improve operational efficiency. The role focuses on developing predictive and prescriptive analytics, leveraging PI Historian data, and translating business needs into actionable insights.

Responsibilities include modeling strategies tailored to site conditions, collaboration with process engineers and operations teams, and delivering scalable solutions across facilities.

Qualifications

• 10+ years of experience in Data Science and Advanced Analytics in manufacturing.
• Proven experience with PI Historian (OSIsoft/AVEVA PI System) and industrial time-series data.
• Strong background in developing optimization models for manufacturing operations focused on energy efficiency.
• Ability to translate business problems into analytical solutions.
• Experience collaborating with operations, process engineers, and stakeholders.

Responsibilities

• Analyze manufacturing processes, energy consumption patterns, and constraints to identify optimization opportunities.
• Develop predictive, prescriptive, and optimization models to reduce energy use and boost efficiency.
• Leverage PI Historian and other data sources to generate actionable insights.
• Define modeling strategies aligned with business objectives and site conditions.
• Build replicable analytical frameworks across facilities.
• Partner with stakeholders to drive adoption and value realization.
• Conduct root cause analysis and identify key parameters affecting energy performance.
• Monitor model performance and improve accuracy and impact.
• Communicate complex findings to technical and non-technical audiences.

Skills

Data science & analytics

Business problem translation

Cross-functional collaboration

Manufacturing operations experience

Tools

PI Historian

Python

SQL

Databricks

Azure

Time-series data

Job description

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.