Role Overview

We are seeking an experienced Senior Risk Data Scientist to join our dynamic team. In this role, you will lead the development and implementation of advanced data analytics, machine learning models, and predictive algorithms focused on risk, weather, and high impact weather events. You will collaborate closely with cross-functional teams, including meteorologists, fire behavior analysts, and software engineers, to enhance our modeling capabilities and deliver actionable insights to our utility clients.

Responsibilities

• Develop and implement predictive models for wildfire risk assessments and power outage prediction. This includes statistical modeling and working with extremely large WRF (Weather Research and Forecasting) datasets.
• Work with large datasets, including satellite imagery, weather data, wildfire data, and utility infrastructure information.
• Collaborate with cross-functional teams including product managers, engineers, and domain experts to build solutions that address customer needs.
• Design and conduct experiments to validate models and improve predictive accuracy.
• Communicate findings and actionable insights to customers and stakeholders.
• Coordinate and optimize existing data production pipelines that includes aggregating, cleaning, and processing shapefiles and NetCDF data.

Requirements

Required

• Degree in Data Science, Statistics, Computer Science, Applied Mathematics, or a related field, Master’s or Ph.D. preferred.
• 5+ years of experience in data science, machine learning, or a related field.
• Technical Skills:
  • Strong programming skills in Python.
  • Strong background in statistical modeling, predictive analytics, and algorithm development.
  • Proven experience with geospatial analysis and time-series modeling.
  • Experience with big data technologies (i.g. Hadoop, Spark, etc.) and cloud computing platforms (e.g. AWS, Azure, etc.) is a plus.
• Excellent problem-solving skills, attention to detail, and an ability to work in a fast-paced, collaborative environment.
• Strong communication skills to convey complex technical concepts to non-technical stakeholders.

Preferred

• Familiarity with wildfire science, environmental modeling, risk modeling, or utility operations is a plus.
• Proficiency with data visualization tools (e.g. Plotly, Matplotlib)
• Experience leading data science projects from conception to deployment.