Ambitious junior Data Scientist

Do you want to embark on a steep and fun learning curve in one of the most dynamic industries for the largest offshore wind operator in the world?

Join us and become our new Data Scientist in our front-running Diagnostics department in Wind Power Operations. Here you will be a part of our team of eight highly skilled and professional colleagues, which works in close collaboration with the daily business to deliver the best in class advice to optimise the operations of our offshore portfolio of turbines. You will work with production data from our wind turbines around the globe and on extracting insights from our large data source, making them transparent to the sites to ensure data-driven decisions in the daily operations.

The department is part of Wind Power, which has 1800 employees and is one of four business units in DONG Energy. Wind Power is the world’s largest developer and operator of offshore wind power, and we use our unique knowledge in all phases of our wind turbine projects. During the last 20 years, we have developed and constructed the largest portfolio of offshore wind farms in Northern Europe, and we are expanding with international activities in the US and Asia-Pacific. 
You will be based at our office in Gentofte in the Greater Copenhagen area. However, you should expect some travelling in relation to your work. 
 
Your key tasks will be to 

• assist technical departments with analysis on production data 
• extract insights from our alarm data and present/communicate this to your stakeholders 
• run our condition monitoring models with daily analysis and dialogue to the technical people for validation and actions 
• help maintain the SQL and Python frameworks in the department 
• create and maintain SpotFire Dashboards (visualisation and analysis of performance).

Moreover, you will help develop, operate and maintain our wind turbine Condition Monitoring models (CM) and data insights to predict and prevent turbine failures to reduce downtime and cost. The scope includes wind turbine drive-train monitoring (gearbox, main bearing) as well the other components of the asset. You should have experience with advanced time series analysis, machine learning, and have knowledge on SQL and NO SQL frameworks, as our data sources vary from unstructured to structured, both in temporal and spatial domain.

Your qualifications and core competences include that you   

• have a master's degree or PhD in Mathematical Modelling, Statistics, Machine Learning or other relevant fields 
• have strong interest in coding in R, Python, MATLAB, SQL and the ability to implement and to design systems with modern technologies like NoSQL databases 
• have a flair for technical insights into physical systems, ie wind turbines or other relevant technical insights and want to work in close cooperation with technical hands-on people 
• have worked with time series analysis, machine learning, statistics and scientific computing 
• are analytical and can see and understand issues from different customer perspectives and can understand translate this knowledge into results. 
• are either a newly graduated or have some experience. We will scope the role to the experience. The most important thing is your attitude.

Furthermore, you have been a top performer in within your field of study and preferably, you have some experience from working with, eg, data analytics and modelling from either work or besides your studies. You have strong collaboration and communication skills and you are a great team player.

We offer 
A unique and challenging job where you have every opportunity to develop your skills, when working on optimising the operations of some of the world's largest offshore wind projects. You will be assigned mentors in the team to secure a strong and fast development of your technical and analytical skillset to secure you continuously can take on more complex tasks, projects and roles.

In DONG Energy Wind Power, we have a high level of expertise and many complex and challenging work tasks. We work goal-oriented and efficiently with some of the world's largest offshore wind projects, and we are committed to reducing the cost of electricity.

Contact us 
Please do not hesitate to contact Kenneth Klynge, Head of Diagnostics and Fleet Monitoring, on telephone +45 9955 2948 if you want to know more about the position.

We look forward to receiving your application, CV and diplomas as electronic files as soon as possible and no later than 1 June 2017, as we will be conducting interviews on a continuous basis. 

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