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Quantitative Portfolio Analyst Jobs (NOW HIRING)

Brown Advisory

Portfolio Analyst

Norfolk, VA · On-site

Participate in portfolio management activities for Balanced multi-asset class portfolios; each ... Strong quantitative, analytical, and interpersonal skills * Bachelor's degree in Finance, Economics ...

Brown Advisory

Portfolio Analyst

Baltimore, MD · On-site

Participate in portfolio management activities for Balanced multi-asset class portfolios; each ... Strong quantitative, analytical, and interpersonal skills * Bachelor's degree in Finance, Economics ...

Brown Advisory Incorporated

Portfolio Analyst

Baltimore, MD · On-site

$75K - $90K/yr

Participate in portfolio management activities for Balanced multi‑asset class portfolios; each ... Strong quantitative, analytical, and interpersonal skills * Bachelor's degree in Finance, Economics ...

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Quantitative Portfolio Analyst information

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$56.5K

$133.9K

$240K

How much do quantitative portfolio analyst jobs pay per year?

As of Sep 13, 2026, the average yearly pay for quantitative portfolio analyst in the United States is $133,877.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,500.00 and $145,500.00 per year, depending on experience, location, and employer.

What is a quantitative portfolio analyst?

Quantitative Portfolio Analysts are finance professionals who use mathematical models, statistical techniques, and data analysis to manage and optimize investment portfolios. They evaluate financial data, assess risk, develop trading strategies, and monitor portfolio performance to maximize returns while managing risk. Their work often involves programming, data mining, and collaborating with portfolio managers to make informed investment decisions.

What are some common challenges faced by quantitative portfolio analysts when integrating new data sources into existing investment models?

Quantitative Portfolio Analysts often encounter challenges when integrating new data sources, such as ensuring data quality, consistency, and compatibility with existing modeling frameworks. Handling large, unstructured, or alternative data requires rigorous validation and preprocessing to avoid introducing biases or errors into the models. Additionally, analysts must collaborate closely with data engineers, IT teams, and portfolio managers to effectively incorporate new insights while maintaining model transparency and regulatory compliance.

What are the key skills and qualifications needed to thrive as a quantitative portfolio analyst, and why are they important?

To thrive as a Quantitative Portfolio Analyst, you need strong quantitative analysis skills, a background in finance or mathematics, and typically a relevant degree such as in statistics, mathematics, or financial engineering. Familiarity with programming languages like Python, R, or MATLAB, as well as experience with portfolio management systems and data analysis tools, is essential. Attention to detail, problem-solving abilities, and effective communication skills help you translate complex data insights into actionable investment strategies. These skills ensure accurate analysis, effective risk management, and the ability to contribute to data-driven portfolio decisions.

What is the difference between Quantitative Portfolio Analyst vs Quantitative Analyst?

AspectQuantitative Portfolio AnalystQuantitative Analyst
Primary FocusManaging and optimizing investment portfolios using quantitative modelsDeveloping and implementing quantitative models for various financial applications
Work EnvironmentAsset management firms, hedge funds, investment banksFinancial institutions, trading firms, research departments
Required CredentialsDegree in finance, mathematics, or related field; often CFA or similar certificationsDegree in quantitative fields; certifications like CFA or FRM beneficial

While both roles involve quantitative skills and financial modeling, the Quantitative Portfolio Analyst primarily focuses on managing investment portfolios, whereas the Quantitative Analyst develops models used across various financial functions. The roles often overlap but differ in their core responsibilities and application areas.

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What states have the most Quantitative Portfolio Analyst jobs?

States with the most job openings for Quantitative Portfolio Analyst jobs include:

What are popular job titles related to Quantitative Portfolio Analyst jobs?

For Quantitative Portfolio Analyst jobs, the most frequently searched job titles are:

Quantitative Portfolio Analyst jobs near you
Infographic showing various Quantitative Portfolio Analyst job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 91% Full Time, 6% Part Time, and 2% Contract. Highlights an 82% Physical, 4% Hybrid, and 14% Remote job distribution, with an average salary of $133,877 per year, or $64.4 per hour.

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Cambridge, MA • On-site

Risk Analytics Company
See more jobs at Risk Analytics Companyexternal

Full-time

Re-posted 8 days ago

Job description

Ph.D. Graduate Intern – Quantitative Portfolio Risk Analytics (Cross-Disciplinary)

Position Overview
We are seeking an exceptional Ph.D. graduate student to join our team as a Quantitative Portfolio Risk Analytics Intern. This role focuses on developing and applying advanced analytical methods to understand portfolio risk, market structure, and complex financial systems.
We are intentionally recruiting from cross-disciplinary, research-driven backgrounds. Doctoral candidates from fields such as physics, astrophysics, math, applied mathematics, statistics, engineering, economics, computer science, quantum computing, biotech, and other data-intensive sciences are strongly encouraged to apply—especially those interested in translating rigorous quantitative methods into real-world financial applications.
Key Responsibilities
  • Develop and enhance quantitative models for portfolio risk, including factor-based and statistical approaches 
  • Analyze large, high-dimensional financial datasets to uncover structure, dependencies, and sources of risk 
  • Design and implement analytical tools and pipelines using Python and SQL 
  • Contribute to model validation, backtesting, and performance evaluation 
  • Collaborate with risk, engineering, and data teams to improve model scalability and data infrastructure 
  • Communicate complex quantitative insights through clear visualizations and technical summaries 
  • Apply advanced methodologies from your discipline (e.g., stochastic modeling, optimization, machine learning, or geometric/topological approaches) to improve risk analytics 
Required Qualifications
  • Currently enrolled in a graduate Ph.D. program in a highly quantitative field (e.g., Math, Applied Mathematics, Physics, Astrophysics, Statistics, Computer Science, Engineering, Financial Engineering, Economics, Biotech or other data-driven disciplines) 
  • Strong foundation in probability, statistics, and numerical methods 
  • Proficiency in Python (NumPy, pandas, or similar) and/or SQL 
  • Experience working with large datasets and implementing quantitative models 
  • Ability to think rigorously about complex systems and translate theory into practical solutions 
Preferred Qualifications
  • Familiarity with quantitative finance concepts (e.g., portfolio theory, factor models, volatility modeling, Value-at-Risk) 
  • Experience with scientific computing, optimization, or machine learning 
  • Background or research in cross-disciplinary areas such as: 
    • Statistical physics, complex systems, or network theory 
    • Applied or computational mathematics 
    • Machine learning or probabilistic modeling 
    • Quantum computing or advanced optimization techniques 
    • Topological data analysis or geometric data methods 
  • Prior research, publications, or project work demonstrating advanced quantitative modeling 
What You’ll Gain
  • Exposure to real-world portfolio risk problems at the intersection of finance and advanced analytics 
  • Opportunity to apply cutting-edge academic methods in a production environment 
  • Collaboration with a highly quantitative, cross-disciplinary team 
  • Experience working with large-scale financial data and modern analytics infrastructure 
  • Mentorship and potential pathway to full-time quantitative roles 
Duration & Compensation
  • Internship: Summer 2026, with potential to extend 
  • Paid internship (competitive, based on experience and location)