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Opis pracovnej ponuky

Ready to revolutionize the future of energy with your data expertise? As a Data Scientist in the Modelling & Analytics team at Vestas, you’ll be at the forefront of developing innovative models and tools, working with a diverse global team to shape the future of wind turbine technology. Vestas Technology & Operations > Research & Development (R&D) > Plant Design & Risk ModellingModelling & Analytics is anchored in Vestas R&D. Vestas R&D is where new product ideas and technologies are developed, matured, tested, and improved. To put it in short, Vestas R&D is the cornerstone of Vestas - we are shaping the future of modern energy. Modelling & Analytics consists of highly skilled, international, highly experienced, cross-discipline employees located across Portugal, Denmark and India, where data gets transformed and utilized to bring insights into various value streams in Vestas. We encourage a culture based on accountability and give employees the chance to create meaningful, real-world impact through their work. We also cultivate employee performance and growth by providing an inclusive, motivating environment with collaboration at its core. You will experience a team of great diversity both within competencies, experience, gender, and nationality.Responsibilities

  • Take ownership of a designated area of the project, ensuring clarity in objectives and driving results with a proactive, self-directed approach. Autonomy is essential, but contributions must remain aligned with the overarching goals of the project and organization
  • Collaborate effectively with team members to maintain open communication and ensure alignment across the team. Your role will require a balance of independent decision-making and active teamwork, with a strong sense of accountability for your assigned outcomes
  • Embrace a mindset of continuous improvement and learning. Be open to experimentation, adapt to changing requirements, and apply feedback loops to refine your approach, ensuring that your work evolves with the needs of the project
  • Contribute to the development of models and tools for validating wind turbine and wind farm solutions, leveraging data-driven insights to enhance efficiency, accuracy, and innovation
  • Prioritize high standards in development work, demonstrating initiative and commitment to delivering results that meet or exceed expectations
  • Collaborate with internal stakeholders to ensure solutions are aligned with business requirements, while remaining adaptable to evolving demands and challenges

Qualifications

  • BSc. or MSc. in engineering, statistics, mathematics, computer science, or a related field
  • Experience with data and statistical analysis
  • Expertise in wind energy, wind farm modeling and optimization
  • Proficiency in Python/R, with experience in SQL and cloud platforms like MS Azure (knowledge of Databricks and Dataiku Data Science Studio is a plus)
  • Familiarity with data mining, data engineering, and data visualization tools. Experience with R Shiny or other frontend visualization tools is advantageous

Competencies

  • A constant growth mindset is essential, as you’ll be expected to stay current with emerging technologies and new methods. The ability to adapt quickly and effectively to changes in project scope, requirements, or technology is critical
  • You thrive in a collaborative environment, working seamlessly with diverse teams and stakeholders. You value communication and teamwork, recognizing that collective success depends on mutual trust and alignment
  • You take full responsibility for your area of the project, demonstrating initiative and decision-making that drives meaningful progress. Accountability is key to ensuring that objectives are met with precision and quality
  • You can manage complex projects with multiple moving parts, while maintaining focus on both the big picture and the finer details. You work efficiently under deadlines, always prioritizing quality and results
  • Fluent in English with the ability to clearly articulate complex ideas to technical and non-technical stakeholders alike

What we offerIf you would like to join an innovative and international environment, with great possibilities for personal development and the best of colleagues, then Vestas and Modelling & Analytics offers just that. With 29,000 employees globally, we are a diverse team united by a common goal: to power the solution - today, tomorrow, and far into the future. Join us in the fight for a more sustainable world. 

 

Additional information  The primary work location is in Aarhus, Denmark. To be considered for this role, you must apply online before October 13, 2024. We will review applications on an ongoing basis. We can withdraw from the job and reserve the right to do so at any time, including before the advertised closing date.

Požiadavky na pracovné miesto
  • BSc. or MSc. in engineering, statistics, mathematics, computer science, or a related field
  • Experience with data and statistical analysis
  • Expertise in wind energy, wind farm modeling and optimization
  • Proficiency in Python/R, with experience in SQL and cloud platforms like MS Azure (knowledge of Databricks and Dataiku Data Science Studio is a plus)
  • Familiarity with data mining, data engineering, and data visualization tools. Experience with R Shiny or other frontend visualization tools is advantageous
Podrobné informácie o pracovnom mieste
Odvetvie:
Work experience:
Work experience is required
Oblasť vzdelania:
Between 2 and 5 years
Jazykové zručnosti:
  • English
  • Very good
Required skills:
analyse big data, apply statistical analysis techniques, data mining, Python (computer programming)
Platové rozpätie:
Not provided
Date of expiry:

About organisation

Workindenmark is the national public employment service for qualified international candidates looking for a job in Denmark, and Danish companies searching for foreign candidates. Workindenmark is part of the Danish Ministry of Employment and member of European Employment Service (EURES).At workindenmark.dk, we provide information, guidance and access to digital self-service tools to bring… Find out more