Principal Data Scientist

Job Description – Principal Data Scientist (Transmission ROW Risk Analytics) Job Title: Principal Data Scientist – Transmission ROW Risk Analytics Location: Dublin, CA (Hybrid – 1–2 days onsite weekly) Duration: 12 Months Contract Pay Rate: $140–180/hr on W2 Work Authorization: Local candidates only We are seeking a highly analytical and mission-driven Principal Data Scientist to support the development of advanced quantitative risk analysis and predictive analytics capabilities for Transmission Right of Way (ROW) Risk Reduction initiatives. The ideal candidate will leverage statistical modeling, machine learning, and geospatial analytics to identify, quantify, and prioritize transmission ROW risks impacting safety, reliability, asset integrity, and wildfire prevention. Key Responsibilities Quantitative Risk Modeling • Develop and implement quantitative risk frameworks to assess transmission ROW encroachments. • Design analytical models and risk-scoring methodologies to estimate event likelihood and operational impact. • Evaluate multiple risk dimensions including: • Public and employee safety • Grid reliability and outage exposure • Wildfire and ignition risks • Regulatory compliance exposure • Asset integrity and operational impact Predictive Analytics & Machine Learning • Build predictive models to forecast safety and reliability events related to ROW encroachments. • Apply advanced analytical techniques including: • Logistic Regression • Survival / Time-to-Event Modeling • Random Forests & Gradient Boosting • Bayesian Modeling • Scenario Simulation & Monte Carlo Analysis • Geospatial & Spatiotemporal Analytics • Identify leading risk indicators such as: • Proximity to energized assets • Clearance violations • Asset age and condition • Inspection findings • Environmental and weather conditions • High Fire Threat District (HFTD) exposure Data Integration & Pipeline Development • Aggregate and structure data from GIS, inspections, outage history, vegetation management, asset management, and operational systems. • Develop scalable analytical pipelines for forecasting, prioritization, and risk scoring. • Assess data quality, lineage, and completeness while recommending improvements. • Collaborate with IT and data engineering teams to support scalable analytics deployment. Decision Support & Visualization • Translate complex model outputs into actionable business insights and prioritization strategies. • Develop dashboards and visualization tools using Power BI, Tableau, or similar platforms. • Support leadership and regulatory reporting with analytical narratives and business cases. Model Monitoring & Continuous Improvement • Establish validation and monitoring processes for model performance and explainability. • Conduct back-testing, sensitivity analysis, and scenario testing. • Continuously refine methodologies based on new operational data and business requirements. Cross-Functional Collaboration • Partner with engineering, wildfire mitigation, compliance, transmission operations, GIS, and risk management teams. • Communicate technical findings effectively to both technical and executive stakeholders. • Facilitate workshops to define risk taxonomy, thresholds, and mitigation strategies. Required Qualifications • Bachelor’s degree in Data Science, Statistics, Computer Science, Engineering, Applied Mathematics, Operations Research, or related quantitative field. • 5+ years of experience in: • Data Science • Predictive Analytics • Quantitative Risk Modeling • Statistical Analysis • Strong proficiency in: • Python • R • SQL • Experience with machine learning, forecasting, feature engineering, and data wrangling. • Ability to work with large, complex datasets from multiple enterprise systems. • Strong communication and stakeholder management skills. Preferred Qualifications • Master’s or PhD in a quantitative discipline. • Experience in electric utility, transmission operations, wildfire mitigation, or infrastructure risk analytics. • Hands-on experience with GIS and geospatial risk modeling. • Familiarity with: • Transmission asset data • ROW management systems • Inspection and outage history • Utility asset health analytics • Experience in regulated industries requiring explainable and auditable models. • Exposure to cloud analytics and model productionization. Technical Skills • Programming: Python, R, SQL • Analytics: Statistical Modeling, Machine Learning, Forecasting, Optimization • Visualization: Power BI, Tableau, Matplotlib • Geospatial: ArcGIS, QGIS, GeoPandas • Modeling Concepts:Classification Models • Risk Scoring Frameworks • Hazard / Survival Models • Explainable AI • Monte Carlo Simulation Key Competencies • Strong analytical and problem-solving abilities • Structured thinking and business acumen • Ability to work in ambiguous and evolving environments • High attention to detail and analytical rigor • Excellent written and verbal communication skills • Ability to balance advanced modeling with operational usability Additional Information • Hybrid role based in Dublin, CA with occasional travel to Oakland, Concord, and field locations. • Client laptop and PPE will be provided if required. • Internet/phone reimbursement may be available with prior approval.