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Python Quantitative Algorithmic Trading Jobs in Ashburn, VA

... including market, trade, counterparty, collateral, margin, and reference data used in risk ... algorithms using programming languages and tools such as MATLAB, Python, SQL, Java, and Excel/VBA.

Job Title: Quantitative Analyst Location: Onsite, Washington, DC (1100 15th Street NW) Schedule ... Python . * Hands-on experience with C++ . * Solid knowledge of capital markets products (trading ...

... Python/R quantitative libraries, graph databases, or network science frameworks). * Strong ... Understanding of diverse data sources across global economics, financial networks, trade flows ...

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Python Quantitative Algorithmic Trading information

See Ashburn, VA salary details

$100.2K

$173.6K

$265.4K

How much do python quantitative algorithmic trading jobs pay per year?

As of Sep 1, 2026, the average yearly pay for python quantitative algorithmic trading in Ashburn, VA is $173,565.00, according to ZipRecruiter salary data. Most workers in this role earn between $137,500.00 and $203,500.00 per year, depending on experience, location, and employer.

What is Python quantitative algorithmic trading?

Python Quantitative Algorithmic Trading refers to the use of Python programming to develop, test, and implement mathematical models and automated strategies for trading financial instruments. Professionals in this field use quantitative analysis, statistical techniques, and historical data to create algorithms that can execute trades on financial markets without human intervention. Python is widely favored due to its robust libraries, ease of use, and strong community support, making it ideal for handling large datasets and rapid prototyping of trading strategies.

What are the key skills and qualifications needed to thrive as a Python quantitative algorithmic trader?

To thrive as a Python Quantitative Algorithmic Trader, you need strong quantitative analysis, programming expertise (especially in Python), and a solid background in mathematics, statistics, or finance, often supported by a relevant degree. Familiarity with financial data platforms, algorithmic trading systems, and libraries such as pandas, NumPy, and scikit-learn, as well as experience with backtesting frameworks, is essential. Critical thinking, attention to detail, and effective communication help you interpret data, manage risk, and collaborate with team members. These skills ensure effective strategy development, implementation, and adaptation in fast-moving financial markets.

What are some common challenges faced by Python quantitative algorithmic traders, and how can job seekers prepare to overcome them?

Python quantitative algorithmic traders often face challenges such as rapidly changing market conditions, ensuring code efficiency for low-latency execution, and maintaining data integrity across large datasets. Additionally, traders must continuously backtest strategies to avoid overfitting and adapt to evolving regulatory requirements. To prepare, job seekers should strengthen their coding skills with a focus on performance optimization, familiarize themselves with financial data handling, and stay current with industry best practices in both technology and trading strategy development.

What is the difference between Python Quantitative Algorithmic Trading vs Python Quantitative Trading Analyst?

AspectPython Quantitative Algorithmic TradingPython Quantitative Trading Analyst
CredentialsDegree in Computer Science, Finance, or related fields; coding certificationsDegree in Finance, Economics, or related fields; strong analytical skills
Work EnvironmentDeveloping algorithms, coding, backtesting strategiesAnalyzing market data, supporting trading strategies, reporting
Industry UsageFinancial firms, hedge funds, proprietary trading firmsAsset management firms, trading desks, financial institutions

Python Quantitative Algorithmic Traders focus on designing and implementing automated trading algorithms using programming skills, while Python Quantitative Trading Analysts analyze data and support trading strategies without necessarily coding the algorithms themselves. Both roles require strong quantitative skills and familiarity with Python, but their daily tasks and responsibilities differ significantly.

What are popular job titles related to Python Quantitative Algorithmic Trading jobs in Ashburn, VA?

For Python Quantitative Algorithmic Trading jobs in Ashburn, VA, the most frequently searched job titles are:

What job categories do people searching Python Quantitative Algorithmic Trading jobs in Ashburn, VA look for?

The top searched job categories for Python Quantitative Algorithmic Trading jobs in Ashburn, VA are:

Infographic showing various Python Quantitative Algorithmic Trading job openings in Ashburn, VA as of August 2026, with employment types broken down into 2% Internship, 86% Full Time, 5% Part Time, and 7% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution, with an average salary of $173,565 per year, or $83.4 per hour.

Quantitative Analytics Senior

Mclean, VA • On-site


Freddie Mac
Finance and Insurance • 5 - 10K employees

9.2

Company rating: 9.2 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

Good employer

Respectful managers

Learn new skills


Full-time

Re-posted 19 days ago


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


What Freddie Mac employees say

Pay

Hours and flexibility

Workplace

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