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Data Scientist – Wind/Renewable energy

Remote  |  Full Time (pronounced as mind’s eye) has developed a distributed reinforcement learning platform called DeepSim. This platform is deployed at our customers to solve complex optimization problems in verticals such as renewable energy, manufacturing process optimization, automotive, etc. We received multi million venture capital investments to build out our platform and customer base.

We value excellent engineering skills and a drive to learn. We consider these traits as important as having prior platform development experience.

About the Role is applying state-of-the-art machine learning algorithms to the world’s renewable energy challenges, particularly in wind energy, as shown by our joint project on wake steering with Vestas and Microsoft. You will help define, shape, and build out our product offering for renewable energy. Additionally, you may work directly with our customers to support the deployment of our products. For our customers, your work will vary from initial data exploration, to modelling and problem formation, and development of machine learning algorithms. Subspecialties within this broad scope are encouraged. You will work collaboratively with our backend, product, and AI teams.

About the engineering team

We have a supportive engineering environment that encourages our engineers to expand their knowledge and capabilities. Senior engineers regularly provide informal instructions to junior engineers. The skillset of our team is extremely broad with people experts in specific topics such as Reinforcement Learning, GPU computing, data science, programming and cloud computing.


The things we look for

  • Experience in modelling and analysis of: wind farms, storage, and/or grid systems.
  • Good knowledge of the renewable energy field and its business KPIs.
  • Good knowledge of statistics, data analysis, and modelling.
  • Preferably experience with simulation of wind/grid/storage (CFD, NREL simulators such as OpenFAST, etc.).
  • Problem solving skills with respect to approaching a new dataset/customer request and formulating a problem.
  • BS, MS, PhD in quantitative field, such as Physics, Mathematics, Statistics, Engineering, or equivalent practical experience.
  • Experience in Python.

It is a bonus if you also have

  • Experience with some form of Deep Learning and a solid understanding of the foundations.
  • Experience with Reinforcement Learning.
  • Familiarity with software engineering best practices.
  • Experience in a customer facing/communication role.

You are a fit for this role if you have

  • Good written and verbal communication.
  • Demonstrated ability to work with minimal to no supervision.
  • Ability to work remotely with cross-cultural teams.
  • Self-motivation to learn new concepts and an excellent record of execution.
  • A sense of urgency, result orientedness, and excellent ability to prioritize.

Our teams are centered around Amsterdam (the Netherlands), Bangalore (India), and Santa Cruz, California (USA). We are location agnostic, and team members regularly work together from remote locations. We are a small, but growing family of hand-selected experts.

We believe in extreme transparency. Every one of us in knows the general direction of the company, current, and future customer prospects, commercial terms, etc. This enables every one of us to influence the course of the company. Debate and discussions are heavily encouraged. The value statement is not a bunch of words but is a living document that guides all our decisions.

We organize regular training and knowledge-sharing sessions led by your colleagues on a weekly basis. If you are inclined, you can offer the same to your colleagues. Apart from work, you will be able to attend conferences and network with colleagues within the industry. We encourage you to give talks at conferences, meetups and submit papers to publications. The company will guide you through this.

As most of us work in remote locations, we put great emphasis on frequent communication. In addition to regular video chats, we strive to meet in person once a year with families.

This is how we will become a team

Our selection process is friendly and interactive. It will involve solving computer science problems, writing code, and getting to know each other. This will be done in a series of meetings either in person or on video. Typically, you can expect to attend 6 to 8 meetings. Some might say it is a tad too many, but we feel that it is essential for you and us to invest this time in the beginning.

We encourage dialogue so be prepared with all your questions and ask them without hesitation.

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