Senior Data Scientist, Outage & Extreme Weather

About Technosylva

Technosylva is a global leader in wildfire and extreme weather risk mitigation software. The Company’s market-leading solutions, enhanced by AI and machine learning capabilities, provide real-time and predictive insights to support electric utility, insurance and government agency customers.

Technosylva has provided critical solutions for the past 26 years. In 2022 the organization entered a period of significant growth and transformation with investment from TA Associates, a leading growth PE firm, scaling to about 175 employees and offering its product in over 10 countries. In 2024 General Atlantic, a leading global growth investor, announced a strategic growth investment in Technosylva to support the company in its mission.
Role Overview

We are seeking a Senior Data Scientist with deep expertise in modeling the impact of extreme weather on electric grid infrastructure, with a particular focus on transmission outage prediction. In this role, you will design, build, and operationalize machine learning and statistical models that predict weather-driven outages and failures across transmission and distribution systems, directly supporting utility decision-making before and during extreme weather events.

You will work at the intersection of atmospheric science, power systems, and machine learning—combining mechanistic, physics-based understanding of infrastructure failure with data-driven probabilistic methods. Your models will feed real-time operational products used by utilities to anticipate outages, position crews, and manage grid risk during storms, extreme winds, and wildfire conditions.
Responsibilities

- Design, develop, and validate machine learning models to predict transmission outages driven by extreme weather, combining mechanistic and probabilistic approaches.

- Build spatio-temporal models that link weather forecasts to infrastructure failure risk, including probability of failure (POF) estimates for transmission and distribution assets.

- Develop models characterizing the interrelationship between transmission outages, extreme weather events, and wildfire ignition risk.

- Integrate heterogeneous datasets—weather model output, asset and infrastructure data, historical outage records, and geospatial layers—into robust, reproducible modeling pipelines.

- Operationalize research-grade models into fast, reliable production systems suitable for real-time forecasting workflows.

- Evaluate and benchmark model performance against state-of-the-art methods and clearly communicate accuracy, skill, and uncertainty to internal teams and utility customers.

- Collaborate with meteorologists, risk modelers, and software engineers to improve Technosylva ’s outage and extreme weather product capabilities.

- Leverage agentic coding tools throughout the development lifecycle—using AI agents to accelerate model prototyping, pipeline development, testing, and documentation—while maintaining rigorous review and validation standards.

Requirements
Education

- Ph.D. in Environmental Engineering, Atmospheric Science, Civil Engineering, Statistics, Data Science, or a related quantitative field strongly preferred.

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

Professional Experience

- Demonstrated experience developing transmission outage prediction models—this is a core requirement for the role.

- 5+ years of experience (academic or industry) applying statistical modeling and machine learning to grid reliability, storm outage prediction, or related energy-sector problems.

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

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

Modeling & Technical Skills

- Strong grounding in machine learnin