Applied Data Science and Analytics Internship

At Enagás, we take care of the people who drive change. We want your talent to grow in a flexible, diverse environment with a vision for the future.

• 1-year internship in a leading company with a solid track record in the sector ⭐
• Possibility of undertaking a training course through an external entity. Access to training portals and catalogs 📚
• Schedule: full-time. Flexible hours, intensive working day on Fridays, and during the summer months ⏲️
• Competitive remuneration 💶
• Assignment of a tutor who will accompany you throughout your stay 🧑🤝🧑
• Work environment that promotes diversity and equality 👋❤️
• Challenging and innovative projects 💡
• Digitalization and agile working methodologies 💻
• Fruit and coffee in the office ☕

Let's build the future of energy together.

If you believe in energy with purpose and want your talent to make an impact, this is your place.

We are waiting for you!

#TalentoConImpacto #TransiciónEnergética #SomosEnagás #ConLosODS #DiversaInclusiva #EquipoEnagás

• Solid foundations in quantitative reasoning and statistics: exploratory analysis, descriptive and inferential statistics, hypothesis testing, correlation and causality, regression/classification, time series, anomaly detection, and model evaluation.
• Practical knowledge of Python and SQL, preferably used in academic, personal, internship, or final degree/master's projects.
• High analytical curiosity and the ability to formulate questions and hypotheses, test them against data, and question initial interpretations.
• Ability and interest in understanding the physical phenomenon and the industrial process behind the data.
• Ability to visualize, synthesize, and communicate results, clearly differentiating between evidence, hypotheses, conclusions, and limitations.

We will value having curiosity to understand what each piece of data physically represents and how it can be used to improve asset management, as well as having knowledge of Microsoft Fabric, Power BI, Machine Learning, notebooks, Git, and data analysis tools, but we will prioritize analytical capacity and learning potential over prior knowledge of specific tools.

• Higher degree, preferably a final-year student in Mathematics, Statistics, Data Science, Physics, Industrial Engineering, Computer Engineering, Telecommunications Engineering, or other scientific-technical degrees with a strong quantitative component.

• High level of English B2-C1

Boost your career at a company that powers the energy of the future

At Enagás, we have spent more than 50 years guaranteeing something essential: the energy that connects people. Our purpose is clear: to move towards a cleaner, more sustainable and more efficient energy model, driving projects that transform the future.

We have an opening for an intern in the Analytics and Digital Assets Management department, belonging to the General Directorate of Infrastructure , for our headquarters in Madrid (Pº de los Olmos), who wants to be part of a project with real impact. We are especially looking for a person whose natural inclination, when faced with a dataset, is to ask what is happening, why it might be happening, what hypotheses could explain it, what analyses would allow them to be tested, and what we can truly conclude from the available evidence.

During your stay, you will be able to participate in maintenance performance analysis and in new advanced analytics capabilities applied to asset management, such as health indices, condition analysis, risk models, or investment planning support. You will learn to apply data analysis techniques, statistics, and data science to real industrial asset management problems, transforming operational and maintenance data into knowledge that allows for formulating and testing hypotheses, identifying opportunities, and improving decision-making.

The person will join as a transversal Data profile for the Analytics and Digital Assets Management department, collaborating with its three areas of activity: Analytics, Digital Assets, and Asset Management Information and Systems.

• Explore, characterize, and analyze datasets coming from operations, maintenance, and asset management.
• Translate business problems and needs into analytical questions and testable hypotheses.
• Apply exploratory analysis, statistical, and data science techniques to identify patterns, trends, relationships, and anomalies.
• Analyze time series and data related to the behavior and condition of industrial assets.
• Support the monitoring and analysis of indicators associated with the performance of the Maintenance Management Model.
• Participate in the development of advanced analytics capabilities applied to asset management: asset health indices, condition analysis, risk models, investment planning, and other use cases.
• Analyze and characterize the quality of the data used, identifying limitations that may affect the results.
• Work together with operations and maintenance experts to understand the physical meaning of the data and test the plausibility of the results.
• Build visualizations and communicate results, conclusions, uncertainties, and limitations in a way that is understandable for business profiles.
• Document the analyses performed to facilitate their reproducibility and reuse.
• Collaborate transversally on department initiatives where data allows for identifying opportunities, establishing starting points, providing evidence, or measuring results.