Job Title: Data Scientist Transmission ROW Risk Analytics Job ID: 26-02210 Location: Dublin, CA (Hybrid 1 2 days/week onsite; local candidates only) Duration: 12 months on W2 contract
Job Summary
Seeking a Data Scientist to develop quantitative risk models and predictive analytics for Transmission Right of Way (ROW) Risk Reduction. The role involves building machine learning models, integrating enterprise data, and delivering actionable insights to support safety, reliability, wildfire risk mitigation, and operational decision-making.
Key Responsibilities
- Develop quantitative risk and predictive models for transmission ROW encroachments
- Build analytics solutions using Python, R, SQL, and ML techniques
- Perform geospatial and risk analysis using GIS and operational data
- Create dashboards and decision-support tools (Power BI/Tableau)
- Collaborate with cross-functional teams including engineering, GIS, operations, and compliance
- Monitor model performance, validation, and continuous improvements
Required Qualifications
- Bachelor s degree in Data Science, Statistics, Engineering, Computer Science, or related field
- 5+ years of experience in data science, predictive analytics, or risk modeling
- Strong experience with Python, R, SQL, statistical modeling, and machine learning
- Experience working with large, complex datasets and translating insights for business stakeholders
Preferred Qualifications
- Master s or PhD in a quantitative field
- Experience in utility, transmission operations, wildfire risk, or infrastructure analytics
- GIS/geospatial analytics experience (ArcGIS, QGIS, GeoPandas)
- Experience with Power BI/Tableau and cloud analytics environments
- Knowledge of utility risk, reliability, and compliance concepts.
Technical Skills
Python, R, SQL, Machine Learning, Forecasting, GIS, ArcGIS, Tableau, Power BI, ETL, Statistical Modeling, Risk Analytics.
Compensation:
The hourly rate for this position is between $100.00-$120.00 per hour.
Factors which may affect starting pay within this range may include [geography/market, skills, education, experience and other qualifications of the successful candidate].
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