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Manager Quantitative Modeling Jobs in California

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Manager Quantitative Modeling information

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

AspectManager Quantitative ModelingQuantitative Analyst
CredentialsAdvanced degrees (Master's/PhD), certifications like CFA or FRM often preferredBachelor's or Master's degree in finance, mathematics, or related fields
Work EnvironmentLeads teams, oversees model development, strategic planningDevelops models, analyzes data, supports trading or risk management
Employer & IndustryFinancial institutions, hedge funds, asset managersInvestment banks, asset management firms, hedge funds

While both roles involve quantitative skills and financial modeling, the Manager Quantitative Modeling typically focuses on leading teams and strategic oversight, whereas the Quantitative Analyst concentrates on developing and implementing models directly supporting trading or risk decisions.

Is modeling a good paying job?

Manager Quantitative Modeling roles are typically well-compensated, especially in finance and technology sectors, with salaries often exceeding industry averages. These positions require strong analytical skills, proficiency in programming languages like Python or R, and advanced degrees such as a master's or Ph.D., which can contribute to higher pay. Overall, quantitative modeling can be a lucrative career path for those with the right skills and experience.

What does a manager quantitative modeling do?

A manager of quantitative modeling oversees the development and implementation of mathematical and statistical models used to analyze financial data, assess risk, and support decision-making. They often lead teams of analysts and use tools like programming languages and data analysis software to ensure models are accurate and reliable within a financial or risk management environment.

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 Manager Quantitative Modeling jobs in California?

For Manager Quantitative Modeling jobs in California, the most frequently searched job titles are:

What job categories do people searching Manager Quantitative Modeling jobs in California look for?

The top searched job categories for Manager Quantitative Modeling jobs in California are:

What cities in California are hiring for Manager Quantitative Modeling jobs?

Cities in California with the most Manager Quantitative Modeling job openings:

Expert, Quantitative Analyst - Resiliency, Strategy, and Partnerships

PG&E Corporation

Oakland, CA • Hybrid

$129K/yr

Full-time

Re-posted 4 days ago


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.