Principal Data Scientist
Axelon Services Corporation · Oakland, CA · 6 days ago
HybridEngineeringOther
Responsibilities
- Design, manage, and optimize complex, interconnected data pipelines using Palantir Foundry and PySpark.
- Develop intuitive user interfaces to translate advanced analytics into actionable insights.
- Quantify wildfire mitigation program performance on the electric system.
- Create predictive models using Python or PySpark in Foundry or AWS.
- Interpret and represent meteorological data in models combining various data sources.
- Design statistical methodology and architect solutions for risk model outputs.
- Lead the design, development, and execution of scripts, programs, models, and algorithms.
- Educate non-technical community on data science solutions.
- Present findings and make recommendations to senior management.
Requirements
- Master’s Degree in Data Science, Machine Learning, Computer Science, Civil Engineering, Mechanical Engineering, Electrical Engineering, Statistics, or equivalent field.
- Minimum 8 years of experience in Data Science, or 2 years if possessing a Doctoral Degree or higher in relevant fields.
Preferred Skills
- Doctorate Degree in relevant fields.
- Expertise in experimental design and causal inference methods.
- Expertise in statistical methods for time series analysis, statistical modeling, and probabilistic risk assessment.
- Relevant industry experience (electric or gas utility, data science consulting, etc.).
- Familiarity with supervised, unsupervised, deep learning & physics-based methods for modeling electrical infrastructure failure modes.
- Competency with data science standards and processes, including model evaluation, optimization, and feature engineering.
- Proficiency with Python or PySpark, code reviews, and code development best practices.
- Mastery in clearly communicating complex technical details and insights.
- Ability to develop, coach, teach, and mentor others.