Principal Data Scientist Jobs in USA, CA, Dublin | Rose International Job
Rose International
Dublin, CA
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JOB DETAILS
SALARY
$75–$85 Per Hour
JOB TYPE
Temporary
LOCATION
Dublin, CA
POSTED
3 days ago
Required Education: Bachelor’s degree in Data Science, Statistics, Applied Mathematics, Engineering, Computer Science, Operations Research, Economics, or a related quantitative field.Preferred Education: Master’s or PhD in a quantitative discipline.Required Experience, Knowledge & Skills: 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 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. Demonstrated ability to turn ambiguous business problems into structured analytical approaches.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 Geospatial: ArcGIS, QGIS, GeoPandas, spatial analysis techniques Modeling concepts: Classification and probability prediction Risk scoring frameworks Time-to-event / hazard models Explainable AI / interpretable models Scenario analysis and Monte Carlo methodsPreferred Experience, Knowledge & Skills: 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.Job Responsibilities: Quantitative Risk Modeling Develop quantitative risk frameworks to assess the risk posed by encroachments within or adjacent to transmission rights of way. Define risk equations, scoring methodologies, and analytical models that estimate both: Likelihood of an event occurring (e.g., safety incident, reliability event, asset damage, access impairment, wildfire ignition, clearance violation, line contact, third-party interference), and Consequence / impact of that event. Incorporate multiple risk dimensions into a unified analytical framework, including: Public and employee safety Electric reliability / outage exposure Wildfire and ignition risk Regulatory and compliance exposure Asset damage and access limitations Financial and operational impact Predictive Analytics & Machine Learning Build predictive models to estimate the likelihood of future safety or reliability events resulting from existing or emerging encroachments in transmission rights of way. Apply statistical and machine learning techniques such as: Logistic regression Survival analysis / time-to-event modeling Random forests / gradient boosting Bayesian methods Scenario modeling and simulation Geospatial and spatiotemporal modeling Identify leading indicators and risk drivers that increase the probability of an event, such as: 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 High Fire Threat District (HFTD) or other high-risk locations Data Integration & Analytical Pipeline Development 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. Partner with IT, data engineering, GIS, and business teams to improve data architecture and enable scalable model deployment. Decision Support & Program Prioritization Translate model outputs into practical prioritization tools that support program strategy, annual planning, and execution. Develop dashboards, visualizations, and decision-support tools to help the business: Rank encroachments by risk Identify high-priority mitigation opportunities Forecast emerging risk hotspots Evaluate tradeoffs across mitigation options Support resource allocation and investment decisions Support the development of business cases and analytical narratives for leadership, regulators, and governance forums. Monitoring, Validation & Continuous Improvement 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. Continuously improve methodologies as new data sources, field intelligence, and business requirements emerge. Cross-Functional Collaboration 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. Communicate technical findings clearly to both technical and non-technical stakeholders, including senior leadership. 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. **Only those lawfully authorized to work in the designated country associated with the position will be considered.** **Please note that all Position start dates and duration are estimates and may be reduced or lengthened based upon a client’s business needs and requirements.** Benefits: For information and details on employment benefits offered with this position, please visit here. Should you have any questions/concerns, please contact our HR Department via our secure website. California Pay Equity: For information and details on pay equity laws in California, please visit the State of California Department of Industrial Relations' website here. Rose International is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender (expression or identity), national origin, arrest and conviction records, disability, veteran status or any other characteristic protected by law. Positions located in San Francisco and Los Angeles, California will be administered in accordance with their respective Fair Chance Ordinances. If you need assistance in completing this application, or during any phase of the application, interview, hiring, or employment process, whether due to a disability or otherwise, please contact our HR Department. Rose International has an official agreement (ID #132522), effective June 30, 2008, with the U.S. Department of Homeland Security, U.S. Citizenship and Immigration Services, Employment Verification Program (E-Verify). (Posting required by OCGA 13/10-91.).
About the Company
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Rose International
Founded in 1993 by Sue Bhatia, Rose International is one of the nation's leading minority- and woman-owned providers of Staffing and Total Talent Solutions. We serve companies in all 50 states and employ thousands of people across the country.