Senior Data Scientist Manufacturing Sustainability

Navayuvabharat Infotech Llp; Hyderabad; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Kimberly-Clark is seeking a senior data scientist to drive adoption of AI-powered energy optimization across its manufacturing network. You will work with process engineers, energy managers, and data scientists to deploy models that reduce energy consumption and improve efficiency.

You will leverage PI Historian data and other industrial time-series sources, build scalable optimization frameworks, and communicate insights to stakeholders. 10+ years in manufacturing analytics is expected.

Qualifications

• Bachelor's or Master's in Data Science, Engineering, Statistics, Applied Mathematics, or a related field.
• 10+ years of experience in Data Science, Advanced Analytics, or AI within manufacturing environments.
• Proven experience with PI Historian (OSIsoft/AVEVA PI System) and industrial time-series data.
• Strong capability to develop optimization models for energy efficiency and sustainability.

Responsibilities

• Collaborate with clients internal Data Science team to scale and deploy Energy Optimization AI solutions across multiple mills.
• Analyse manufacturing processes, energy consumption patterns, and operating constraints to identify optimization opportunities.
• Develop and enhance predictive, Prescriptive, and optimization models to reduce energy use and improve efficiency.
• Leverage PI Historian and other manufacturing data sources to generate actionable insights and recommendations.
• Define modelling strategies based on business objectives, process understanding, and site conditions.
• Build analytical frameworks that can be replicated across facilities.
• Partner with stakeholders 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 and impact.
• Communicate complex findings to technical and non-technical stakeholders.

Skills

Data Science

Advanced Analytics

Optimization Modeling

Stakeholder Communication

Python

SQL

Time-series Analysis

Root Cause Analysis

Education

Bachelor's or Master's in Data Science

Tools

PI Historian (OSIsoft/AVEVA PI System)

Databricks

Azure

Job description

This role requires a strong understanding of manufacturing processes, energy systems, industrial time-series data, and advanced analytics. The successful candidate will work closely with process engineers, mill leadership, energy managers, and internal data scientists to drive adoption of AI-powered optimization recommendations across Kimberly-Clark's manufacturing network.

Role & responsibilities

• Collaborate with clients internal Data Science team to scale and deploy Energy Optimization AI solutions across multiple mills.
• Analyse 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 modelling 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.

Preferred candidate profile

• Bachelor's or Master's degree in Data Science, Engineering, Statistics, Applied Mathematics, or a related field
• 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.