Cook Systems is looking to solve the business and technical problem of transforming industrial operations through advanced analytics and optimization, supporting their clients' Digital Industrial Transformation strategy.
Requirements
- Specialization in Data Science, Machine Learning, Modeling, Simulation, and/or Optimization.
- Relevant work experience in Data Science techniques and technical skills in developing mathematical optimization solutions for complex real-world problems within chemical industrial operations.
- Strong background in chemical and process engineering with expertise in applying mathematical optimization techniques and using tools like CPLEX and Gurobi.
- Proficient in machine learning, including supervised, unsupervised, and reinforcement learning, with hands-on skills in Python, Azure, and Dataiku.
- Experienced in handling and querying industrial data from historian databases (e.g., PI, IP21) and using tools like Power BI and SEEQ for analysis and visualization.
Responsibilities
- Translate industrial and operational needs into advanced analytics requirements and insights.
- Design and implement industrial data science solutions to optimize performance, quality, and maintenance.
- Develop and deploy energy optimization solutions, including the complete industrialization process.
- Effectively communicate complex analytical results and ideas to stakeholders and decision-makers.
- Train and support engineers in advanced analytics and optimization techniques.
- Research and develop optimization algorithms focusing on energy efficiency and sustainability.
Other
- Master's degree or equivalent in Chemical Engineering, Process Systems Engineering, Mathematics, Computer Science, or a related quantitative field with a strong chemical/process background
- Minimum of 7 years of experience preferred.
- L1-Onsite
