Senior Data Scientist, Outage & Extreme Weather

This is a fully remote position, open to applicants in Colorado.

📋 Description

• Create, enhance, and validate machine learning models aimed at forecasting transmission outages caused by extreme weather conditions.

• Develop spatio-temporal models that connect weather predictions to the risk of infrastructure failures, including estimates for the probability of failure for transmission and distribution assets.

• Construct models that define the interactions between transmission outages, extreme weather occurrences, and the risk of wildfire ignition.

• Combine weather model outputs, asset and infrastructure information, historical outage data, and geospatial layers into reproducible modeling workflows.

• Transition research-grade models into efficient and dependable production systems for real-time forecasting processes.

• Assess and compare model performance against leading-edge methodologies.

• Convey accuracy, skill, and uncertainty metrics to internal teams as well as utility customers.

• Work in collaboration with meteorologists, risk modelers, and software developers to enhance outage and extreme weather products.

• Employ AI agents to expedite model prototyping, pipeline development, testing, and documentation while adhering to stringent review and validation protocols.

⛳️ Requirements

• A Ph.D. in Environmental Engineering, Atmospheric Science, Civil Engineering, Statistics, Data Science, or a closely related quantitative discipline is strongly preferred.

• A master’s degree with significant applied experience in weather-driven outage or infrastructure risk modeling will also be considered.

• Proven experience in developing models for predicting transmission outages.

• A minimum of 5 years of experience (either academic or industry) applying statistical modeling and machine learning to grid reliability, storm outage prediction, or similar challenges within the energy sector.

• Experience collaborating with utilities, ISOs/RTOs, or grid operators on weather-related operational forecasting is highly valued.

• A record of peer-reviewed publications, patents, or deployed production models in areas such as outage prediction, wildfire risk, or extreme weather impacts.

• Strong foundation in ensemble methods, neural networks, probabilistic models, and statistical modeling applied to spatio-temporal challenges.

• Experience integrating physics-based/mechanistic models with data-driven techniques for predicting infrastructure failures.

• Proficiency in working with geospatial data and tools, such as GeoPandas, ArcGIS or equivalent, and extensive multidimensional weather datasets.

• Advanced skills in Python, including libraries like NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch.

• Ability to produce clean, well-documented, production-ready code.

• Capacity to optimize model runtime and computational workflows for real-time operational applications.

• Hands-on experience utilizing agentic coding tools like Claude Code, Cursor, Copilot agents, or similar as integral components of daily development tasks.

• Proficiency in structuring tasks for AI agents by composing specifications, breaking down problems, and providing context.

• Strong judgement in reviewing and validating code generated by agents for scientific accuracy.

• Familiarity with R, SQL, or Julia is an added advantage.

🏝️ Benefits

• No benefits, perks, or compensation extras are specified in the posting.