Operations Economics & Analytics Student Assistant

2024-09-17 | PEAK Wind | Aarhus | Other | Denmark

Perks & Benefits:

Location:
Aarhus

Do you want to improve your knowledge of the economics of renewable energy operations and advanced analytics? Do you want to be part of a determined team, making operations part of daily work life in the Renewable Energy industry? PEAK Wind is looking for an Operations Economics & Analytics Student Assistant to support consultants and specialists in their daily work for customers and internal workstreams.


Trusted Advisors for Developers and Investors for some of the Largest Renewable Assets

At PEAK Wind, we specialise in operations, asset management, and project management of renewable energy assets and take pride in providing best-in-class commercial, financial, and operational advisory and support to our clients. We work with some of the world’s largest infrastructure investments and are proud to count market-leading utilities, investment funds, and IPPs among our clients.


Job Content, Responsibilities, and Possibilities

Based in one of our offices in Europe (Aarhus, Copenhagen, Hamburg, London, or Glasgow), you will be providing support to our internal and external customers within Operations Economics & Analytics. You will become a part of our team, where you will be working closely together with our leading experts within the area. You will have a wide range of tasks including support to operations strategy & business case analysis and will be carrying out computational assessments with standard or advanced numerical codes to support the consulting activities in different disciplines such as operations optimization, wind farm design and logistics, etc. You will also take part (or even take the lead) in the development of such analytical frameworks and get the opportunity to become a part of our growth journey within this field.

As a Student Assistant, we expect that you can work an average of 15-20 hours a week with flexibility for your studies, exam periods, and PEAK Wind’s business needs.

The Operations Economics & Analytics team has strong relationships with international academic institutes and has a relevant track record in co-supervising BSc or MSc Thesis work in the last few years. Thus, the student assistant may set up a thesis in co-supervision between PEAK Wind and the student’s university on a topic relevant to PEAK Wind.


What you Bring and your Qualities

You are studying a relevant bachelor’s or master’s degree within the field of renewable energy, engineering, economics, or math/physics. You have strong academic records and you set high standards for yourself. Further, you have strong analytical skills, basic coding capabilities (e.g. Python) and a structured approach to solving your tasks autonomously. PEAK Wind is a global company, and you must therefore have strong English communication skills. As the position has many interfaces from different disciplines, you also need to possess the ability to professionally communicate to a variety of stakeholders of different backgrounds, internally but also to our clients, including Senior Executives.


We offer a Steep Learning Curve and Accelerated Development

We offer a unique and challenging opportunity to work in “an industry of the future” where you can put theory into practice and grow your capabilities in a fast-growing, international company. You will experience a steep learning curve and accelerated development, and together with the team, you will play an instrumental part in the continued success of PEAK Wind. Above that, you will participate in an entrepreneurial environment focusing on cooperation and a desire to change the status quo.


Interested and want to know more?

If you have any questions or want to know more about the position, please contact People & Development via [email protected]. We look forward to receiving your applications & CVs as soon as possible, latest September 30th, 2024.


Deadline:
30/09/2024, 16:59
Employment type:
Student
Practice group:
Operations Economics & Analytics

Location:
Aarhus, Denmark, Copenhagen, Denmark, Hamburg, Germany, London, England, UK, Glasgow, Scotland, UK

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