Senior Data Scientist Manufacturing Sustainability

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.