Data Scientist - Transmission ROW Risk Analytics

Job Title: Data Scientist Transmission ROW Risk Analytics

Job Location: Dublin, CA

Job Type: Contract

Job Overview:

Pay Range: $158.50hr - $163.50hr

Requirement/Must Have:

• Bachelor s degree in Data Science, Statistics, Applied Mathematics, Engineering, Computer Science, Operations Research, Economics, or a related quantitative field.
• 5+ years of experience in data science, predictive analytics, quantitative risk analysis, or statistical modeling.
• Experience building predictive models using Python, R, SQL, or similar tools.
• Strong knowledge of statistical inference, machine learning, risk modeling, forecasting, feature engineering, and data quality management.
• Experience working with large, complex, and imperfect datasets from multiple business systems.
• Strong analytical, problem-solving, and communication skills.
• Ability to explain technical findings to operational and executive stakeholders.
• Experience translating business problems into structured analytical solutions.

Experience:

• Experience with predictive analytics and machine learning techniques such as logistic regression, survival analysis, random forests, gradient boosting, Bayesian methods, and scenario modeling.
• Experience with geospatial and spatiotemporal modeling techniques.
• Experience developing dashboards and decision-support tools.
• Experience collaborating with cross-functional operational and technical teams.
• Experience with model validation, calibration, sensitivity analysis, and performance monitoring.

Responsibilities:

• Develop quantitative risk frameworks to assess risks associated with transmission ROW encroachments.
• Build analytical models to estimate the likelihood and impact of safety, reliability, wildfire, compliance, and operational events.
• Develop predictive models to identify leading indicators and risk drivers.
• Aggregate, clean, and structure data from GIS, inspections, outage history, incident data, vegetation data, and asset management systems.
• Develop repeatable analytical pipelines for forecasting, trend analysis, and prioritization.
• Create dashboards, visualizations, and prioritization tools to support planning and resource allocation.
• Conduct scenario testing, back-testing, and model performance evaluations.
• Partner with business, engineering, GIS, and IT teams to improve data architecture and model deployment.
• Communicate analytical findings and recommendations to technical and non-technical stakeholders.
• Support business cases and analytical reporting for leadership and governance forums.

Should Have:

• Master s or PhD in a quantitative discipline.
• Experience in electric utility, transmission operations, wildfire risk, asset risk management, or reliability analytics.
• Experience with GIS-based risk modeling and geospatial analytics.
• Familiarity with transmission asset data, inspection data, outage history, and utility asset health data.
• Experience in regulated industries requiring transparency and explainable models.
• Familiarity with cloud analytics environments and productionized machine learning models.

Skills:

• Python.
• R.
• SQL.
• Statistical modeling.
• Machine learning.
• Forecasting.
• Simulation and optimization.
• Data wrangling and ETL concepts.
• Data quality assessment.
• Power BI.
• Tableau.
• ArcGIS.
• QGIS.
• GeoPandas.
• Spatial analysis techniques.
• Classification and probability prediction.
• Risk scoring frameworks.
• Time-to-event and hazard models.
• Explainable AI and interpretable models.
• Scenario analysis and Monte Carlo methods.