Sea Surface Temperature (SST) Data Scientist (m/f/d)

OroraTech
Πλήρης απασχόληση
Αθήνα
The Mission

At OroraTech Germany, we are on a mission to revolutionize how businesses and governments utilize space-based thermal data, specifically focusing on Sea Surface Temperature (SST) data products. We are seeking an experienced SST Data Scientist / Developer to join our team. Your first task will be to create an SST prototype for exploitation in Greece, with a robust global scale-up strategy in mind. This role involves close collaboration with our Data Science, Business Development, Product Development, and Sales teams to drive growth and innovation in sectors such as climate, government, and more.

What You’ll Be Doing

  • Responsible for designing, developing, and deploying an SST data prototype for initial use in Greece, with plans for global expansion.
  • Basis: Level 1 thermal data and OT LST product. Experience with processing low level space data preferred.
  • In charge of leading the technical development of SST data products, ensuring alignment with market needs and customer requirements.
  • Collaborating with the technical team in Germany to ensure the technical feasibility and scalability of SST solutions.
  • Contributing to the calibration and validation strategies to ensure the accuracy and reliability of SST data products.
  • Creating a data processor with operational usage in mind, aimed at scaling up for broader application.
  • Leveraging third-party datasets to enhance SST data products.
  • Conducting research and development to enhance the accuracy and reliability of SST data products.
  • Visualizing concepts to a wide audience and excelling at translating technical insights into business solutions.
  • Monitoring and reporting on the performance of SST data products, including performance metrics and key performance indicators.
  • Providing technical support to Business Development as well as supporting new project acquisitions.

Relevant Skills

  • Minimum of 5 years in data science or related field. Bachelor’s degree in Data Science, Computer Science, Environmental Science, or related field (Master’s or Ph.D. preferred).
  • Strong experience in data science and remote sensing data processing. Experience with LST or SST data products preferred.
  • Knowledge about atmospheric physics and oceanography (i.e. atmospheric correction, emissivity estimation and radiative transfer).
  • Applied programming experience (Python, Docker, gitlab). Familiarity with physical and statistical modeling.
  • Experience in calibration and validation of Earth Observation data products.
  • Excellent problem-solving and analytical skills. Strong communication and teamwork abilities. Ability to visualize concepts and translate technical insights into business solutions. Proactive and results-driven mindset. High adaptability in a fast-paced environment.

We Offer

Benefits

At OroraTech, you can expect a down to earth yet high-caliber work environment. You will be part of the OroraTech team - a talented, international, open-minded team that is highly motivated to create impact. OroraTech allows you to grow on a professional and personal level. Benefits include:

  • Be part of the solution to climate change
  • Ambitious and entrepreneurial company culture with very high standards
  • Insights into the most exciting new technologies and business models
  • A great remote/hybrid office culture, which allows you to be very flexible. Take care of your family? Late sleeper? Early riser? Prefer to work from outside from time to time? We can make all that work.

If you apply: Please always include references of your prior work (for example, your thesis, talks, papers, code repositories, websites, write-ups, articles, apps, exposes, anything), if permissible. Please avoid detailed grade reports and online certificates. We value well-crafted motivation letters stating how you learned about OroraTech, why you think you would be a great addition to the team and why you want to work at a NewSpace start-up. Please also list your earliest starting date and expected salary.

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