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Environmental Algorithms Engineer

BreezoMeter is looking for an Environmental Algorithms Engineer with the creativity, professionalism, and passion to be involved in the research and development of innovative data-driven environmental models and algorithms that impacts the lives of millions of users around the world. In this position, you’ll be working with exceptional people in a multidisciplinary R&D team to create inspiring data-driven solutions that you can be proud of.

We Are Looking For People Who Are

  • Curious and enthusiastic to learn new things
  • Independent in their approach and learning
  • Team players
  • Thoughtful, positive, and proactive
  • Flexible and possess a “can-do” attitude
  • Researchers in the heart with strong mathematical intuitions


  • Work alongside other environmental engineer, software engineers, and data scientists to help developing new environmental algorithms from research to implementation
  • Develop new algorithms and models to bring to life new products and improve existing ones
  • Examine the performance and accuracy of models and algorithms, and be part of the efforts for constant improvement
  • Research for developments in the field, such as new models, and algorithmic solutions to extend and improve the value of our product
  • Locate, examine, validate and integrate new sources of data
  • Learn new skills and become proficient in new disciplines, breaking new grounds to improve the company products


  • Few years of experience developing scientific, statistical or physical algorithms
  • Academic (B.Sc. or higher) degree in Environmental Engineering, Electrical or Aeronautical Engineering, Physics, Math, Computer Science or similar disciplines
  • Very strong analytical skills, ability to analyze and tackle complex algorithmic problems
  • Good communication skills, ability to formulate and articulate the problem in hand, approaches to solutions and results
  • Experience in working with Python and strong technical skills
  • Familiarity with SQL
  • Familiarity with data analysis techniques and tools, preferably in Python

Bonus Points

  • Scientific background and/or practical experience in the air pollution sciences - big advantage!
  • Experience with Python’s data analysis stack (e.g. NumPy, SciPy, Pandas, Matplotlib)
  • Strong SQL skills and familiarity with standard data stores
  • Familiarity with Machine Learning models and techniques
  • Familiarity with Geographical Information Systems (GIS) and geographical data