Develop and Implement Optimization Models Design, develop, and maintain advanced optimization algorithms to improve energy management and operational efficiency, using methods such as mathematical programming (MILP).
Analyze and Interpret Complex Datasets Work with large and diverse data sources to extract meaningful insights, support model calibration, and guide decision-making through data visualization and statistical evaluation.
Integrate Data Science Solutions into Production Collaborate with software engineers, cloud architects, and domain experts to embed models into scalable cloud environments, ensuring stability and performance.
Enhance Automation and Model Performance Continuously monitor, evaluate, and optimize the performance of deployed models while ensuring maintainability and transparency.
Collaborate in Cross-functional, Agile Teams Work in an agile, collaborative environment, contributing your data science expertise to strategic projects and supporting knowledge sharing across teams.
Requirements
Strong experience of 10 years plus in Python and libraries such as pandas, NumPy, scikit-learn, or Pyomo for data analysis and modeling.
Solid understanding of optimization techniques, particularly mixed-integer linear programming (MILP) or related methods.
Hands-on experience working in cloud platforms (e.g., AWS, Azure, or GCP) and with scalable deployment pipelines.
Familiarity with data exploration, processing, and visualization tools to derive actionable business insights.
Bachelor’s or Master’s degree in Computer Science, Mathematics, Engineering, or a related field.
Benefits
Flexible working hours
Work-life-balance
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
PythonpandasNumPyscikit-learnPyomomixed-integer linear programmingoptimization techniquesdata analysisdata visualizationstatistical evaluation