Forecasting Expert

24 hours ago


Singapore beBeeEnergy Full time
Job Title:

Data Analyst - Energy Sector


Job Description

The primary goal of this role is to develop and refine forecasting models that support strategic planning and operational efficiency within the energy sector.

The researcher will analyze historical and real-time data to predict energy demand, supply fluctuations, and market trends, incorporating factors such as weather patterns, consumption behavior, and regulatory changes.

By leveraging advanced statistical and machine learning techniques, the role aims to provide accurate, data-driven insights that inform energy production, distribution, and sustainability initiatives.


Required Skills and Qualifications
  • Master's or PhD in Data Science, Statistics, Energy Systems, Engineering, Applied Mathematics, or a related field.
  • 3–5 years of experience in forecasting, data analysis, or energy research (postdoctoral experience preferred for senior roles).
  • Proficiency in Python, R, or MATLAB.
  • Experience with time series forecasting, machine learning, and statistical modelling.
  • Familiarity with energy data sources and modelling platforms.
  • Certified Energy Manager (CEM) or Data Science/Machine Learning certifications (optional but valuable).

Benefits

This role offers the opportunity to contribute to the development of innovative energy solutions and collaborate with cross-functional teams to ensure forecasts align with business goals.

The successful candidate will have the chance to work on high-profile projects, publish research findings in academic journals or industry reports, and stay up-to-date with advancements in forecasting techniques, energy technologies, and market dynamics.


Others

This is an exciting opportunity for a talented data scientist to join our team and make a meaningful contribution to the energy sector.

The ideal candidate will be passionate about data-driven decision-making, committed to continuous learning, and able to communicate complex ideas effectively to technical and non-technical audiences.



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