Data Scientist - Forecasting

Get AI-powered advice on this job and more exclusive features. Established in 2010, the Energy Research Institute @ NTU (ERI@N) is a pan-university research institute that focuses on systems-level research for tropical megacities. It performs translational research that covers the energy value chain from generation to innovative end-use solutions, motivated by industrialisation and deployment. ERI@N has multiple Interdisciplinary Research Programmes which focus on translational Research, Development & Deployment which focus on specific area of the energy value chain, and a number of Living labs and Testbeds which facilitate large scale technology deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian The primary purpose 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. The researcher will collaborate with cross-functional teams to ensure forecasts align with business goals and contribute to resilient, future-ready energy systems Key Responsibilities Develop Forecasting Models Design and implement statistical and machine learning models to predict energy demand, supply, and market trends. Analyse Energy Data Collect, clean, and interpret large datasets from various sources including smart meters, weather systems, and market reports. Monitor and Validate Model Performance Continuously evaluate forecasting accuracy and refine models to improve reliability and responsiveness. Collaborate with Stakeholders Work closely with energy planners, engineers, and policy teams to align forecasts with operational and strategic goals. Integrate External Factors Incorporate variables such as weather patterns, regulatory changes, and economic indicators into forecasting frameworks. Support Sustainability Initiatives Provide insights that help optimize renewable energy integration and reduce carbon footprint. Communicate Insights Present findings through reports, dashboards, and presentations to technical and non-technical audiences. Stay Current with Industry Trends Keep up-to-date with advancements in forecasting techniques, energy technologies, and market dynamics. Contribute to Research Publications Publish research findings in academic journals or industry reports to advance knowledge in energy forecasting Job Requirements Core Competencies Analytical Thinking Ability to interpret complex datasets and identify patterns, trends, and anomalies. Forecasting & Modelling Expertise Proficiency in time series analysis, regression models, and machine learning techniques relevant to energy forecasting. Technical Proficiency Skilled in tools such as Python, R, MATLAB, SQL, and Excel; familiarity with energy modelling software is a plus. Domain Knowledge Understanding of energy systems, market dynamics, renewable integration, and regulatory frameworks. Communication Skills Capable of translating technical insights into actionable recommendations for diverse stakeholders. Problem-Solving Innovative and solution-oriented approach to addressing forecasting challenges and improving model accuracy. Collaboration & Teamwork Experience working in interdisciplinary teams and engaging with engineers, analysts, and policy experts. Attention to Detail Precision in data handling, model validation, and documentation. Project Management Ability to manage multiple research tasks, meet deadlines, and contribute to long-term strategic goals. Continuous Learning Commitment to staying updated with the latest forecasting techniques, energy technologies, and industry trends Qualification Education: Master’s or PhD in Data Science, Statistics, Energy Systems, Engineering, Applied Mathematics, or a related field. Experience: 3–5 years of experience in forecasting, data analysis, or energy research (postdoctoral experience preferred for senior roles). Technical Skills: Proficiency in Python, R, or MATLAB Experience with time series forecasting, machine learning, and statistical modelling Familiarity with energy data sources and modelling platforms Certifications (Optional but Valuable): Certified Energy Manager (CEM) Data Science or Machine Learning certifications (e.g., from Coursera, edX, or industries bodies We regret to inform that only shortlisted candidates will be notified. Hiring Institution: NTU Seniority level Seniority level Mid-Senior level Employment type Employment type Full-time Job function Job function Engineering and Information Technology Industries Higher Education Referrals increase your chances of interviewing at Nanyang Technological University Singapore by 2x Get notified about new Data Scientist jobs in Singapore, Singapore . 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Location: Singapore, Pedra Branca, SG

Posted Date: 7/10/2025