Senior Machine Learning (Data) Scientist
Spire Global is a space-to-cloud analytics company that owns and operates the largest multi-purpose constellation of satellites. Its proprietary data and algorithms provide the most advanced maritime, aviation, and weather tracking in the world. In addition to its constellation, Spire’s data infrastructure includes a global ground station network and 24/7 operations that provide real-time global coverage of every point on Earth.
Spire Global is seeking a Data Scientist to support its development of artificial intelligence, statistical and probabilistic weather forecast products. This job involves building better weather forecasts using Spire in-house data streams and machine learning techniques. The successful candidate will join the Machine Learning team under the weather division, at the Spire office in Luxembourg, and will work closely with team members in Spire’s Boulder, CO, USA, office.
Responsibilities of your role:
The candidate will work with the team to develop advanced Machine Learning (ML) based weather technologies for global and regional forecasting. At Spire, we have large datasets of satellite and simulation data. As a Data Scientist you will work alongside other teams (Software engineers and Product development) to develop models and put them into production.
- Propose and implement innovative machine learning models to increase the forecast skills of Spire weather products.
- Develop and maintain ML software packages (developing, testing, and verification).
- Develop and implement state of the art weather post-processing techniques using ML.
- Working with meteorological data sets from various sources.
- Presenting research findings at scientific conferences or workshops.
- PhD or MS degree in Engineering, Computer Science, Applied Mathematics, Atmospheric Science or equivalent.
- Working experience with state-of-the-art machine learning models in particular deep learning, CNN, LSTM, probabilistic models, etc.
- Knowledge to understand the leading academic literature in seasonal and sub-seasonal forecasting
- Working experience bringing data science pipelines into production.
- 2+ years experience working with GNU/Linux.
- 2+ years experience working with Python, including packing/deployment (Conda, PyP, Anaconda), experience and exposure to the scientific Python stack (NumPy, Pandas), and advanced machine learning libraries (Tensorflow, Pytorch, SciPy and Scikit-Learn).
- Prior experience working with modern software engineering best practices: revision-control systems, testing & code quality tools, and continuous integration.
Nice to haves:
- Experience with numerical weather prediction, weather applications, and/or data formats common in the weather domain (BUFR, GRIB, NetCDF).
- Experience with distributed parallel programming systems, frameworks, libraries such as DASK, Spark, Hadoop, etc.
- Experience working on HPC systems.
- Experience with compiled languages (i.e. C++).
- Experience with cloud platforms (AWS, Google Cloud, etc.).
Spire is Global and our success draws upon the diverse viewpoints, skills and experiences of our employees. We are proud to be an equal opportunity employer and are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or veteran status.