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Executive Quantitative Modeling Jobs in California

Quantitative Developer

San Francisco, CA · On-site

$180K - $280K/yr

You'll work alongside Poesis' Chief Scientist, CEO and engineering leadership to turn large-scale data and quantitative research into models, signals and tools that drive investment decision-making.

You'll work alongside Poesis' Chief Scientist, CEO and engineering leadership to turn large‑scale data and quantitative research into models, signals and tools that drive investment ...

... executive-level materials, value models, and pricing strategy for industry-specific use cases. You ... Strong analytical and quantitative modeling skills, including experience building value models ...

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... the intersection of quantitative modeling, risk management, and high-performance system ... Partner directly with AI, Engineering, and Executive teams to surface deep insights, predictive ...

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Executive Quantitative Modeling information

What are some common challenges faced by professionals in executive quantitative modeling roles and how are they typically addressed?

Professionals in Executive Quantitative Modeling roles often face the challenge of translating complex quantitative models into actionable insights for stakeholders who may not have technical backgrounds. Balancing model sophistication with interpretability is key, as is ensuring data quality and regulatory compliance. Collaboration with cross-functional teams, such as IT, risk, and business units, is essential to integrate models into business processes and to gain buy-in from decision-makers. Regular communication, thorough documentation, and ongoing validation of model performance help address these challenges effectively.

What is the difference between Executive Quantitative Modeling vs Quantitative Analyst?

AspectExecutive Quantitative ModelingQuantitative Analyst
CredentialsAdvanced degrees (MBA, PhD), certifications like CFA or FRMBachelor's or Master's in Finance, Mathematics, or related fields
Work EnvironmentStrategic decision-making, senior management meetingsData analysis, model development, reporting
Industry UsageFinancial institutions, hedge funds, asset managementInvestment banks, asset managers, financial firms

Executive Quantitative Modeling professionals focus on high-level strategic models and decision-making, often working with senior leadership. Quantitative Analysts typically handle data analysis, model building, and implementation at a more technical level. Both roles require strong quantitative skills, but differ in scope and responsibilities.

What is executive quantitative modeling?

Executive quantitative modeling is a high-level role that involves developing, overseeing, and interpreting complex mathematical and statistical models to inform business strategies and decision-making. Professionals in this position typically lead teams that create models for risk assessment, financial forecasting, portfolio management, or pricing strategies. They work closely with senior executives to translate quantitative insights into actionable business plans. This role requires deep expertise in mathematical modeling, data analysis, and proficiency with advanced analytics tools and programming languages.

What are the key skills and qualifications needed to thrive as an executive in quantitative modeling?

To excel as an Executive in Quantitative Modeling, you need advanced expertise in mathematical modeling, statistical analysis, and financial theory, typically supported by a graduate degree in a quantitative discipline such as mathematics, statistics, finance, or engineering. Proficiency with programming languages (like Python, R, or MATLAB), data analytics platforms, and experience with industry-standard risk management or financial modeling systems is highly valued. Leadership, strategic thinking, and strong communication skills set outstanding executives apart by enabling them to guide teams and translate complex models into actionable business insights. These capabilities are crucial for driving data-driven decision-making and maintaining a competitive edge in complex financial environments.
What are the most commonly searched types of Quantitative Modeling jobs in California? The most popular types of Quantitative Modeling jobs in California are:
What are popular job titles related to Executive Quantitative Modeling jobs in California? For Executive Quantitative Modeling jobs in California, the most frequently searched job titles are:
What job categories do people searching Executive Quantitative Modeling jobs in California look for? The top searched job categories for Executive Quantitative Modeling jobs in California are:
What cities in California are hiring for Executive Quantitative Modeling jobs? Cities in California with the most Executive Quantitative Modeling job openings:
Infographic showing various Executive Quantitative Modeling job openings in California as of August 2026, with employment types broken down into 1% Internship, 90% Full Time, 5% Part Time, and 4% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution.

Expert, Quantitative Analyst - Resiliency, Strategy, and Partnerships

Pacific Gas and Electric Company

Oakland, CA • Hybrid

$129K/yr

Full-time

Posted 24 days ago


Pacific Gas and Electric Company rating

9.0

Company rating: 9.0 out of 10

Based on 46 frontline employees who took The Breakroom Quiz

3rd of 53 rated energy and utility


Job description

Requisition ID # 172355 

Job Category: Business Operations / Strategy 

Job Level: Individual Contributor

Business Unit: Strategy & Growth

Work Type: Hybrid

Job Location: Oakland

Department Overview

The System Performance, Reliability and Resiliency Strategy team within the overall Electric Transmission and Distribution Engineering organization is responsible for planning, organizing, and managing the resources necessary to successfully execute PG&E's Electric Reliability Strategy and initiatives. Within this department the Resiliency Strategy and Partnerships team will lead the long-term reliability and resiliency strategy. This work will include driving the development of related IEEE/IEC, FERC/NERC, EEI/IUNG/AEIC standards.  

Position Summary

Leads the application of advanced analytics, including data science, machine learning, operations research, engineering, and economic modeling, to analyze complex energy systems and inform high-impact business, regulatory, and investment decisions. Serves as a technical expert, shaping analytical approaches and driving the development of quantitative models that support enterprise strategy, policy, financial planning, and procurement.

Designs, develops, and oversees the execution of sophisticated models, algorithms, and decision-support tools using large, diverse datasets. Provides leadership across the full analytics lifecycle, including data engineering, modeling, and visualization, while ensuring technical rigor, scalability, and continuous improvement. Partners with cross-functional teams, senior leadership, and external stakeholders to resolve complex analytical challenges and align solutions with business objectives.

Translates complex technical analyses into clear, executive-level insights and recommendations that influence PG&E's strategic and regulatory positions. Builds and maintains strong internal and external relationships and represents the company in industry forums, contributing thought leadership in quantitative modeling and energy system analytics.

This position follows a hybrid work model, requiring employees to report to their assigned office location at least two or three days per week. The remaining days may be worked remotely, depending on business needs. The headquarters is located in the Oakland General Office.

PG&E is providing the salary range that the company, in good faith, believes it may pay for this position at the time of the job posting. This compensation range is specific to the job's locality.  The actual salary paid to an individual will be based on multiple factors, including, but not limited to, specific skills, education, licenses or certifications, experience, market value, geographic location, collective bargaining agreements, and internal equity. Although we estimate the successful candidate hired into this role will be placed toward the middle or entry point of the range, the decision will be made on a case-by-case basis based on these factors. This job is also eligible to participate in PG&E's discretionary incentive compensation programs.

A reasonable salary range is:
Bay Area Minimum: $129,000
Bay Area Mid-Point: $168,000
Bay Area Maximum: $207,000

Job Responsibilities

   Works independently with internal and external stakeholders with guidance on the most complex issues, development of new and innovative data and quantitative modeling, research, etc.
   Extracts, transforms, and loads data from dissimilar sources across internal and external sources.
   Proactively identifies future challenges, develops recommendations for resolution, evaluates, and develops new analytic tools and processes for the department.
   Responsible for maintaining and updating complex models and complex analytical assumptions.
   Develops or assists in the development of industry-wide best practices.
   Coaches, mentors, and trains others.
   Serves as an expert witness or expert witness assistant.
   Prepares and may lead the preparation of testimony on complex analyses and policy issues
   Examines alternate solutions to a problem, effectively troubleshoots various issues and analyses, and provides findings and recommendations for internal clients and external stakeholders.
   Provides critical and insightful assessments of third-party work products and comparisons to internal work products.

Qualifications

Minimum:

   Bachelor's Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, Business, or equivalent field.
   Job-related experience 6 years, OR Master's Degree and 5 years job-related, OR Doctorate and 3 years

Desired:

   Advanced Degree
   Job-related experience 8 years

Knowledge, Skills, Abilities, and Competencies: 

   Expertise in quantitative energy system modeling and analysis frameworks and techniques.
   Knowledge of data science, machine learning, operations research, engineering, or economics analytical modeling tools and programming languages. 
   Experience at electric or natural gas utilities, independent power producers, wholesale energy market participants, regulatory agencies, consulting firms, or similar organizations
   Demonstrated ability to take a conceptual issue and independently design and complete innovative analysis to draw meaningful conclusions. 
   Demonstrated ability to lead large and complex projects working with cross-functional teams. 
   Excellent oral and written communication skills and ability to concisely convey information based on unique audience needs.
   Demonstrated capability in planning and prioritizing work to meet commitments aligned with organizational goals.


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