Atmospheric Scientist

Atmospheric Scientist

Requirements

• Have earned a PhD in Atmospheric Science, Meteorology, or a closely related quantitative field.
• Have significant experience working with atmospheric models (NWP and/or AI models) and large meteorological datasets.
• Possess strong proficiency in Python programming.
• Are comfortable working in a Linux environment and using Git for version control.
• Have experience running computational jobs on clusters or cloud computing environments.
• Have a demonstrated ability to analyze and interpret complex scientific data and model outputs.
• Are an effective communicator, able to explain complex weather concepts to non-experts.
• Are naturally curious and eager to learn about new domains, particularly energy systems and time-series modeling.
• Thrive in a fast-paced, dynamic startup environment where priorities can evolve.

Responsibilities

• Engaging in more open-ended research and development to build or refine our own weather modeling capabilities.
• Fine-tuning existing state-of-the-art AI models (e.g., based on GenCast, AIFS, and NeuralGCM).
• Post-processing existing SOTA AI forecasts to debias and recalibrate for our downstream power predictions.
• Incorporating and evaluating model changes, pushing the boundaries of how we forecast weather variables relevant to the energy sector.
• Educate and inform the broader team about atmospheric phenomena and weather forecasting concepts.
• Potential to publish research and findings derived from your work, contributing to the scientific understanding at the intersection of atmospheric science and energy, where appropriate and aligned with business goals.
• Surveying and evaluating the suitability of various Numerical Weather Prediction (NWP) and commercially available AI weather forecast products for our power production and price models.
• Rigorously evaluating and monitoring the performance of integrated weather products, analyzing their impact across different regions, timeframes, and weather regimes.
• Working with external data providers (like NOAA) and internal engineers to define data requirements.
• Work with engineers to build, monitor, and maintain data ingestion pipelines.
• Develop evolving metrics for AI weather models for our unique specifications.
• Work with engineers to set up, run, and monitor SOTA AI weather forecasts on our GPU cluster.
• You might also apply your modeling skills to improve generic time series models for power production or energy price forecasting, using ML libraries like PyTorch or JAX.
• Write and maintain significant Python code within a Git-based software development workflow.
• Continuously learn about grid power modeling and the intricacies of energy markets.

Preferred Qualifications

No preferred qualifications provided.