The role involves applying machine learning and emerging AI methods to improve business operations and optimize supply chains within the climate technology sector
Job Summary
The role involves applying machine learning and emerging AI methods to improve business operations and optimize supply chains within the climate technology sector.
Candidates will lead projects across forecasting, simulation modeling, and LLM-based applications while collaborating with global engineering and operations teams.
Copeland offers a hybrid work model with competitive benefits including medical insurance, 401(k), and flexible time off plans for employees committed to sustainability.
Matching Summary
The role involves applying machine learning and emerging AI methods to improve business operations and optimize supply chains within the climate technology sector.
Skills & Requirements
Must-have
7+ years of data science experience
Proficiency in Python and Git
Strong statistical modeling skills
Experience with ETL and data validation
Ability to communicate with non-technical stakeholders
Nice-to-have
Interdisciplinary background in manufacturing
Interest in Generative AI applications
Experience with Azure DevOps and Agile
Knowledge of HVACR industry specifics
Background in academic research translation
Key Requirements
Bachelor's degree in Data Science or related field
7 or more years of relevant experience
Legal authorization to work in the US (no sponsorship)
Hybrid work availability in St. Louis, Sidney, or Kennesaw
Work Rights
Must be legally authorized to work in the United States