Data Scientist_Engineering

Job Description:

• To conduct data analysis and visualization;
• Utilize Python Programming and/or other software program to develop internal tools for data analysis, visualization and AI optimization;
• To build and evaluate data modeling, machine learning and mathematical optimization;
• Create and manage the AI development and production infrastructure;
• Transform machine learning models into APIs that can be integrated with other applications;
• Conduct statistical analysis and interpret the results to guide and optimize the organization’s decision-making process;
• Build AI models from scratch and help product managers and other stakeholders with analysis and implementation;
• Collaborate across teams to help with AI adoption and best practices;
• Participate in energy performance analysis/audits;
• Ensure the respect of processes, procedures, and operational modes defined by the Group and participate in their continuous improvement;
• Maintain a close relationship with internal and external stakeholders;
• Other ad hoc projects as assigned

Qualifications:

• Bachelor’s degree or above in Computer Science, Data Science, Statistics, Engineering (e.g. Mechanical Engineering, Building Services Engineering, Energy Engineering, Electrical Engineering, or relevant disciplines) or a related field with a strong foundation in programming, algorithms, and data structures is crucial;

Requirements:

• 3 years relevant experience in python programming, data modeling and machine learning;
• Proficiency in Python: Demonstrated experience with Python, including core libraries (NumPy, pandas, matplotlib, scikit-learn, pytorch, tensorflow) for data manipulation, analysis, and visualization;
• Understanding of machine learning algorithms and techniques, including supervised and unsupervised learning methods;
• Familiarity with SQL and database management systems for data extraction and manipulation;
• Knowledge of different APIs and communication open protocols in IoT, BMS, PLC system, etc…;
• Background in optimization: familiarity with optimization techniques (linear programming, nonlinear programming, convex optimization) and their application to data-driven problems;
• Excellent attention to detail, strong numeracy & analytical skills;