Dublin
Principal Data Scientist Dublin, CA (Hybrid 1-2 days in a week) 12 Contract LOCAL CANDIDATES ONLY The role is Hybrid. 1-2 days a week in Dublin. There may be times when we need to travel to other locations such as Oakland, Concord, or field sites around the service area. Client laptop will be providedPPE: Client will provide, if needed, hardhat, vest, safety glasses, etc. **With prior Manager approval, may submit expense, at a set amount for internet/phone reimbursements Position Summary: • We are seeking a highly analytical and mission-driven Data Scientist to support the development of a quantitative risk analysis and predictive analytics capability for Transmission Right of Way (ROW) Risk Reduction Strategy., • This role will help design and operationalize data-driven methods to quantify risk, prioritize encroachments, and predict the likelihood of safety and reliability events associated with transmission right of way encroachments., • The successful candidate will partner with cross-functional teams across electric operations, asset management, vegetation management, engineering, risk, compliance, GIS, inspection, and program management to translate field, asset, and operational data into actionable insights., • The Data Scientist will build models that enable proactive decision-making by identifying where encroachments pose the greatest potential threat to public safety, worker safety, grid reliability, asset integrity, and wildfire risk., • This role is ideal for someone who combines deep technical expertise in statistical modeling and machine learning with the ability to work in complex operational environments and communicate insights to business and executive stakeholders. Key Responsibilities Quantitative Risk Modeling • Develop quantitative risk frameworks to assess the risk posed by encroachments within or adjacent to transmission rights of way., • Public and employee safety, • Electric reliability / outage exposure, • Wildfire and ignition risk, • Regulatory and compliance exposure, • Asset damage and access limitations, • Logistic regression, • Survival analysis / time-to-event modeling, • Random forests / gradient boosting, • Bayesian methods, • Scenario modeling and simulation, • Proximity to energized assets, • Encroachment type and severity, • Clearance deficits, • Structure condition / asset age, • Land use and development patterns, • Historical incident patterns, • Inspection findings, • Environmental and weather conditions, • Access constraints, • Aggregate, clean, and structure data from multiple enterprise and operational systems, including GIS, asset management, inspections, outage history, incident data, vegetation data, work management, and field observations., • Develop repeatable analytical pipelines to support risk scoring, trend analysis, forecasting, and prioritization., • Assess data quality, completeness, and lineage; identify data gaps and recommend improvements to enable stronger analytics., • Rank encroachments by risk, • Identify high-priority mitigation opportunities, • Forecast emerging risk hotspots, • Evaluate tradeoffs across mitigation options, • Support resource allocation and investment decisions, • Establish model validation, calibration, and performance monitoring processes to ensure analytics remain accurate, explainable, and fit for purpose., • Track model precision, recall, false positives/negatives, drift, and operational usefulness over time., • Conduct sensitivity analyses, scenario testing, and back-testing against historical events., • Partner closely with subject matter experts in transmission operations, inspection, engineering, wildfire mitigation, risk management, land/ROW, and compliance to ensure models reflect real-world operating conditions., • Facilitate discussions to define risk taxonomy, modeling assumptions, thresholds, and action triggers., • 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., • Statistical inference, • Machine learning, • Risk modeling, • Forecasting, • Feature engineering, • Data wrangling and data quality management, • Experience working with large, complex, and imperfect datasets from multiple business systems., • Ability to explain technical results to operational and executive audiences in a clear, concise, and decision-oriented manner., • Master’s or PhD in a quantitative discipline., • Experience in electric utility, transmission operations, wildfire risk, asset risk management, infrastructure risk, public safety risk, or reliability analytics., • Experience with geospatial analytics, including GIS-based risk modeling., • Familiarity with transmission asset data, ROW management, encroachment data, inspection data, outage/event history, or utility asset health data., • Experience in regulated industries where transparency, traceability, and model explainability are essential., • Knowledge of safety and reliability risk concepts in utility operations., • Experience developing dashboards or decision-support tools using Power BI, Tableau, or similar platforms., • Familiarity with cloud analytics environments and productionizing models for business use. Technical Skills • Programming: Python, R, SQL, • Analytics: Statistical modeling, machine learning, forecasting, simulation, optimization, • Data tools: Data wrangling, ETL concepts, data quality assessment, • Visualization: Power BI, Tableau, matplotlib, seaborn, or similar, • Classification and probability prediction, • Risk scoring frameworks, • Time-to-event / hazard models, • Explainable AI / interpretable models, • Strong problem-solving and structured thinking, • Ability to work across technical and operational disciplines, • High attention to detail and analytical rigor, • Strong business acumen and decision orientation, • Comfort working in evolving, ambiguous problem spaces, • Ability to balance model sophistication with usability and explainability, • Excellent written and verbal communication skills Applicant Notices & Disclaimers • For information on benefits, equal opportunity employment, and location-specific applicant notices, click ___ At SPECTRAFORCE, we are committed to maintaining a workplace that ensures fair compensation and wage transparency in adherence with all applicable state and local laws. This position's pay is: $165/daily.
Cleaning
Driver & Delivery
Kitchen Porter
Chef & Cook
Construction & Trades
Security
Fast Food
Salon & Beauty
Office & Admin
Retail
Sales & Marketing
Warehouse
Customer Service
Host & Hostess
Barista
Entertainment
Accounting & Finance
Animal Care
Art, Media, Design
Bar Staff
Child Care
Education
Engineering
Events & Promotion
Fashion
Healthcare
Information Technology
Legal
Management
Manufacturing
Online Jobs
Science
Sports & Wellness
Writing & Editing
Other