EDP Renewables APAC is the main subsidiary of EDP Group, a global leader in the renewable energy sector and one of the world’s largest wind producers. With its headquarters in Singapore, EDP Renewables is the leading sustainable development hub for the Asia Pacific region with activities across nine different markets. Our activities are focused on the design, development, management, and operation of renewable energy sources, namely solar, wind, as well as new technologies such as storage.
EDP is a global energy group leading the Energy Transition, Innovation and Sustainability. Using the technology of the future, we create solutions highly focused on the needs of our people and our customers, never neglecting our role and contributions to society. To achieve our goals, we aim to attract diverse people with high potential through the professional opportunities we create.
Join us to be part of a renewable energy leader that reinvests in society through sustainable projects and social as well as cultural causes. You will have the opportunity to actively participate in our global transformation, by changing tomorrow now.
Summary:
We are looking for a curious, technically strong undergraduate intern to join our E and C team and help us unlock the value of our Construction Management Tool (CMT) data. This is a hands:on, exploratory role at the intersection ofdata engineering, AI, and real:world industrial operations.
If you are looking for an internship where you will spend your time on toy datasets and predefined exercises – this is not it. You will work with production data from live renewable energy projects, develop a deep understanding of how that data is structured, and – critically -define how AI can be applied to it. The use cases you identify and the groundwork you lay will directly feed into the AI initiatives this team pursues next.
This is early:stage, high:ownership work. The right candidate will be energised by ambiguity, driven by curiosity, and excited by the idea of shaping something from the ground up.
Responsibilities
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Data architecture mapping- understand the CMT data model end:to:end: tables, relationships, data flows, and how project information is captured across the solar, wind, and BESS delivery lifecycle.
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Data catalogue development- document data assets in a structured, accessible catalogue: field definitions, data types, quality observations, and coverage gaps.
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Exploratory data analysis- query and profile the data to surface patterns, anomalies, and signals relevant to project delivery performance.
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AI use case identification- this is where it gets interesting. Drawing on your understanding of the CMT data and the broader E and C workflow, you will identify and document potential AI/ML applications across the business: predictive analytics, anomaly detection, scheduling optimisation, procurement insights, process automation, and beyond. For each candidate use case, you will assess feasibility, data readiness, and potential business value – building a tangible AI opportunity map for the team.
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AI/ML groundwork- assess the data landscape for ML readiness; identify what data preparation, enrichment, or pipeline work would be required to bring priority use cases to life.
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Collaboration- work closely with E and C project managers, planners, and engineers to contextualise data with domain knowledge and pressure:test your ideas against operational reality.
Requirements
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Penultimate or final year undergraduate student in Data Science, Artificial Intelligence, Machine Learning, or a related quantitative discipline.
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Proficiency in SQL – comfortable writing non:trivial queries against relational databases
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Python for data analysis (pandas, numpy, matplotlib/seaborn or equivalent)
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Familiarity with data engineering concepts: schemas, ETL pipelines, data lineage
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Exposure to ML workflows – feature engineering, model evaluatio
Salary: Competitive
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