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Quantitative Finance Analyst Jobs in Virginia (NOW HIRING)

Coursework or work experience applying finance, statistics, mathematics, data science, and computer programming techniques to quantitative modeling problems in the financial industry. * Relevant ...

Exceptional quantitative, analytical, and organizational skills * Previous accounting or finance related internships strongly preferred * Knowledge of GAAP, secondary mortgage markets, and fixed ...

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Quantitative Finance Analyst information

See Virginia salary details

$56K

$132.7K

$237.9K

How much do quantitative finance analyst jobs pay per year?

As of Aug 31, 2026, the average yearly pay for quantitative finance analyst in Virginia is $132,729.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,500.00 and $144,300.00 per year, depending on experience, location, and employer.

What is a quantitative finance analyst?

A Quantitative Finance Analyst, often called a 'quant,' is a professional who uses mathematical models, statistics, and computer programming to analyze financial markets and securities. Their work typically involves developing trading algorithms, assessing risk, and pricing complex financial instruments. Quants play a critical role in investment banks, hedge funds, and asset management firms, helping organizations make data-driven investment decisions. They usually have strong backgrounds in mathematics, statistics, finance, and programming.

What are the key skills and qualifications needed to thrive as a quantitative finance analyst?

To thrive as a Quantitative Finance Analyst, you need a strong background in mathematics, statistics, programming, and finance, often supported by a degree in a quantitative field such as mathematics, finance, or engineering. Proficiency in technical tools like Python, R, MATLAB, and familiarity with financial modeling platforms and databases is typically required, along with certifications such as CFA or FRM being advantageous. Strong analytical thinking, attention to detail, and effective communication skills help you interpret data, collaborate with teams, and present actionable insights to stakeholders. These skills are crucial for developing accurate financial models, managing risk, and driving data-driven decision-making in fast-paced financial environments.

What are some common challenges quantitative finance analysts face when developing and implementing new financial models?

Quantitative Finance Analysts often encounter challenges such as ensuring data quality and accuracy, managing the complexity of mathematical models, and aligning models with real-world market behavior. They must also navigate regulatory constraints and work closely with IT and trading teams to integrate models into production systems. Staying updated on the latest quantitative techniques and adapting to rapidly changing market conditions are crucial for success in this role.

What is the difference between Quantitative Finance Analyst vs Quantitative Research Analyst?

AspectQuantitative Finance AnalystQuantitative Research Analyst
Required CredentialsDegree in Finance, Economics, or Mathematics; often CFA or FRM certificationsDegree in Mathematics, Statistics, or Computer Science; similar certifications may apply
Work EnvironmentFinancial institutions, hedge funds, asset management firmsResearch firms, hedge funds, financial technology companies
Employer & Industry UsageUsed for developing trading strategies, risk management, and financial modelingFocuses on developing new models, algorithms, and research for trading and investment

Both roles involve quantitative skills and financial knowledge, but Quantitative Finance Analysts typically focus on applying models to trading and risk management, while Quantitative Research Analysts emphasize developing new research methods and algorithms for investment strategies.

Infographic showing various Quantitative Finance Analyst job openings in Virginia as of August 2026, with employment types broken down into 85% Full Time, 13% Part Time, and 2% Contract. Highlights an 79% Physical, 8% Hybrid, and 13% Remote job distribution, with an average salary of $132,729 per year, or $63.8 per hour.

Quantitative Analytics Senior

Freddie Mac

Mclean, VA • On-site

Full-time

Re-posted 19 days ago


Freddie Mac rating

9.2

Company rating: 9.2 out of 10

Based on 5 frontline employees who took The Breakroom Quiz


Job description

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it's at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose.
Position Overview:
Freddie Mac's Investments & Capital Markets Division is seeking a Quantitative Analytics Senior to develop, implement, monitor, and execute quantitative models that support counterparty credit risk management, fixed-income derivatives valuation, and related business and risk management decisions.
The candidate should be self-motivated, has a strong quantitative and computational background, and communicates effectively with technical and business stakeholders. As part of the Models & Analytics team, this role will primarily support Freddie Mac's Counterparty Credit Risk Management and Asset-Liability Management functions, with responsibilities spanning model development, implementation, monitoring, data processes, documentation, and business user support.
Our Impact:
This role focuses on the design, development, implementation, and monitoring of quantitative models and analytics that support counterparty credit risk, exposure measurement, derivatives valuation, and related risk management activities.
The models and analytics developed by the team provide key inputs into counterparty credit risk management, portfolio management, business reporting, and risk-informed decision-making across the division.
Your Impact:
• Develop, implement, and maintain quantitative models primarily for counterparty credit risk measurement, with additional coverage of interest rates, derivatives valuation, and valuation components related to mortgage products.
• Implement models and analytics using programming languages and tools such as MATLAB, Python, SQL, Java, and Excel/VBA.
• Manage data processes that support model development, implementation, monitoring, and reporting, including data sourcing, validation, reconciliation, quality controls, and issue resolution.
• Analyze large financial datasets, including market, trade, counterparty, collateral, margin, and reference data used in risk analytics.
• Design and execute model monitoring plans, produce performance monitoring reports, and respond to questions from business users, model validators, and other stakeholders.
• Prepare detailed model documentation and technical documentation for internally developed and vendor models in accordance with model risk standards.
• Support business users by monitoring model use and performance, producing business-line reports, and explaining model analytics in clear business terms.
• Collaborate with Counterparty Credit Risk Management, model governance, model validation, technology, and other stakeholders to support model implementation, controls, and ongoing use.
• Develop practical solutions to complex business problems and support the implementation and validation of business strategies.
• Proactively partner with teammates and business users to develop practical analytical approaches and advance new ideas.
Qualifications:
  • Doctorate or Master's degree + 3 years relevant experience in quantitative finance, economics, statistics, mathematics, or a related quantitative field.
  • Coursework or work experience applying finance, statistics, mathematics, data science, and computer programming techniques to quantitative modeling problems in the financial industry.
  • Relevant coursework may include statistics, mathematical programming, optimization, machine learning and AI, computational methods, design and analysis of algorithms, derivatives, and Monte Carlo methods.
  • Coursework or work experience developing models, analytics, and algorithms using programming languages and tools such as MATLAB, Python, SQL, Java, and Excel/VBA.
  • Experience sourcing, analyzing, validating, and reconciling large financial datasets used in model development, execution, monitoring, and risk reporting.
  • Familiarity with counterparty credit risk concepts, including initial margin, variation margin, PD, LGD, EAD, exposure measurement, and related regulatory requirements.
  • Familiarity with regression models, stochastic process modeling, and Monte Carlo simulation.
  • Experience with financial derivatives, valuation, risk analytics, and Greeks.
Keys to Success in this Role:
  • Strong quantitative, technical, research, and programming skills.
  • Strong analytical skills with attention to detail, data quality, and model controls.
  • Self-motivated and able to own projects, manage priorities, and work efficiently under tight deadlines.
  • Ability to understand complex business requirements, define relevant analytical problems, and translate model results into business terms.
  • Strong verbal and written communication skills, with the ability to collaborate effectively across technical, business, and governance teams.

Current Freddie Mac employees please apply through the internal career site.
We consider all applicants for all positions without regard to gender, race, color, religion, national origin, age, marital status, veteran status, sexual orientation, gender identity/expression, physical and mental disability, pregnancy, ethnicity, genetic information or any other protected categories under applicable federal, state or local laws. We will ensure that individuals are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
A safe and secure environment is critical to Freddie Mac's business. This includes employee commitment to our acceptable use policy, applying a vigilance-first approach to work, supporting regulatory mandates, and using best practices to protect Freddie Mac from potential threats and risk. Employees exercise this responsibility by executing against policies and procedures and adhering to privacy & security obligations as required via training programs.
CA Applicants: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
Notice to External Search Firms: Freddie Mac partners with BountyJobs for contingency search business through outside firms. Resumes received outside the BountyJobs system will be considered unsolicited and Freddie Mac will not be obligated to pay a placement fee. If interested in learning more, please visit www.BountyJobs.com and register with our referral code: MAC.
Time-type:Full time
FLSA Status:Exempt
Freddie Mac offers a comprehensive total rewards package to include competitive compensation and market-leading benefit programs. Information on these benefit programs is available on our Careers site.
This position has an annualized market-based salary range of $126,000 - $190,000 and is eligible to participate in the annual incentive program. The final salary offered will generally fall within this range and is dependent on various factors including but not limited to the responsibilities of the position, experience, skill set, internal pay equity and other relevant qualifications of the applicant.

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About Freddie Mac

Sourced by ZipRecruiter

Today, Freddie Mac makes home possible for one in four home borrowers and is one of the largest sources of financing for multifamily housing. Join our smart, creative and dedicated team and you'll do important work for the housing finance system and make a difference in the lives of others.

Industry

Finance and insurance

Company size

5,001 - 10,000 Employees

Headquarters location

McLean, VA, US

Year founded

1970