Senior Data Scientist, Outage & Extreme Weather

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

📋 Description

• Design, develop, and validate machine learning models aimed at predicting transmission outages caused by extreme weather conditions.

• Construct spatio-temporal models that connect weather forecasts to the risk of infrastructure failure, including estimates of failure probabilities for both transmission and distribution assets.

• Create models that illustrate the relationship between transmission outages, extreme weather occurrences, and risks associated with wildfire ignition.

• Integrate outputs from weather models, asset and infrastructure data, historical outage records, and geospatial layers into comprehensive, reproducible modeling pipelines.

• Transition research-grade models into efficient, reliable production systems for real-time forecasting operations.

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

• Convey accuracy, skill, and uncertainty metrics to internal teams and utility clients.

• Work collaboratively with meteorologists, risk modelers, and software engineers to enhance Technosylva’s products related to outages and extreme weather.

• Utilize agentic coding tools to expedite model prototyping, pipeline development, testing, and documentation while upholding stringent review and validation standards.

⛳️ 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 along with significant practical experience in modeling outage or infrastructure risk driven by weather will also be considered.

• Proven experience in developing models for predicting transmission outages.

• Over 5 years of relevant experience (in academic or industry settings) applying statistical modeling and machine learning to grid reliability, storm outage prediction, or similar energy-sector challenges.

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

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

• A solid foundation in ensemble methods, neural networks, probabilistic models, and statistical modeling for spatio-temporal challenges.

• Experience in merging physics-based/mechanistic models with data-driven strategies for predicting infrastructure failures.

• Proficiency in handling geospatial data and tools, including GeoPandas, ArcGIS or similar, as well as large multidimensional weather datasets.

• Advanced skills in Python, including frameworks such as NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch; familiarity with R, SQL, or Julia is an advantage.

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

• Practical experience with agentic coding tools like Claude Code, Cursor, Copilot agents, or equivalent as an integral part of daily development activities.

• Proficient in drafting clear specifications, breaking down problems, and providing context for AI agents.

• Strong judgment in reviewing and validating code generated by agents, particularly regarding scientific accuracy in modeling pipelines.

🏝️ Benefits

• Competitive annual salary.

• Private health insurance coverage.

• A flexible benefits plan that allows customization of part of your compensation package to fit personal needs.

• An annual bonus based on individual performance and overall company results.

• Flexible working hours.

• Options for remote work.