We are looking for a Data Scientist Transmission ROW Risk Analytics for our client in Dublin, CA
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.