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How much do senior quantitative developer jobs pay per year?

As of Sep 10, 2026, the average yearly pay for senior quantitative developer in the United States is $172,864.00, according to ZipRecruiter salary data. Most workers in this role earn between $160,000.00 and $186,000.00 per year, depending on experience, location, and employer.

What is a senior quantitative developer?

A Senior Quantitative Developer is an experienced professional who combines advanced programming skills with deep knowledge of mathematical and statistical modeling to design, implement, and optimize complex financial algorithms and trading systems. They work closely with quantitative analysts and traders to translate mathematical models into efficient, production-ready code, often focusing on areas such as risk management, pricing, and market data analysis. In addition to strong coding abilities, typically in languages like C++, Python, or Java, they are expected to have expertise in financial markets, data structures, and performance optimization. Senior Quantitative Developers often mentor junior team members and contribute to the strategic direction of technology and model development within their firm.

What are the key skills and qualifications needed to thrive as a senior quantitative developer?

To thrive as a Senior Quantitative Developer, you need a strong background in mathematics, statistics, computer science, and financial theory, typically supported by an advanced degree in a quantitative field. Proficiency in programming languages such as Python, C++, or Java, and experience using quantitative libraries, databases, and version control systems are essential, alongside knowledge of relevant industry tools like MATLAB or R. Strong problem-solving skills, attention to detail, and the ability to communicate complex concepts clearly are crucial soft skills for this role. These abilities enable effective development and implementation of quantitative models, ensuring robust financial analysis and supporting critical business decisions.

How does a senior quantitative developer typically collaborate with quantitative researchers and traders?

A Senior Quantitative Developer works closely with quantitative researchers to translate their mathematical models into robust, production-ready code. They also partner with traders to understand their workflow needs and ensure that trading systems are reliable, efficient, and responsive to market conditions. Effective communication is key, as the developer must bridge the gap between research insights and operational trading platforms. This collaboration often involves iterative feedback, rapid prototyping, and ongoing support to adapt systems to new strategies or market data.

What is the difference between Senior Quantitative Developer vs Quantitative Analyst?

AspectSenior Quantitative DeveloperQuantitative Analyst
Required CredentialsAdvanced degrees in math, finance, or computer science; programming skillsSimilar educational background; strong analytical skills
Work EnvironmentDevelops trading algorithms, implements models, collaborates with tech teamsPerforms data analysis, risk assessment, supports trading strategies
Employer & Industry UsageFinancial firms, hedge funds, investment banksAsset management firms, hedge funds, banks

The main difference is that Senior Quantitative Developers focus on building and implementing trading models and software, while Quantitative Analysts primarily analyze data and develop trading strategies. Both roles require strong quantitative skills, but the developer role emphasizes programming and system development, whereas analysts focus more on data analysis and research.

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Senior Quantitative Developer jobs near you
Infographic showing various Senior Quantitative Developer job openings in the United States as of September 2026, with employment types broken down into 85% Full Time, 3% Part Time, and 12% Contract. Highlights an 79% Physical, 4% Hybrid, and 17% Remote job distribution, with an average salary of $172,864 per year, or $83.1 per hour.

Principal Quantitative Developer

Chicago, IL • On-site

Fidelity Investments
Investment Management and Consulting Services • 10K+ employees
Learn more about Fidelity Investmentsexternal

Full-time

Posted 15 days ago

Key responsibilities

  • Designs and develops investment risk analytics platforms to support quantitative risk analytics and data-driven risk modeling.

  • Produces quantitative risk reporting and analytics to support monitoring of market, credit, liquidity, and derivatives risks.

  • Supports reporting and visualization solutions to enable effective consumption of portfolio risk analytics.

Fidelity Investments rating

8.7

Company rating: 8.7 out of 10

Based on 274 frontline employees who took The Breakroom Quiz

16th of 154 rated financial services

Job description


Note: Fidelity will not provide immigration sponsorship for this position.
Position Description:
Designs and develops investment risk analytics platforms to support quantitative risk analytics and data- driven risk modeling within an investment management context, with a focus on alternative investment products. Develops and maintains linear and non-linear risk analytics to support model calculation, validation, and stress analysis for portfolios and derivative instruments. Develops and enhances risk reporting processes to support derivative exposure measurement, leverage risk monitoring, and Value at Risk (VaR) analysis. Develops quantitative analytics using Python and SQL to compute portfolio-level risk measures and support ongoing risk monitoring. Supports reporting and visualization solutions using Python-based frameworks to enable effective consumption of portfolio risk analytics. Analyzes, cleanses, and prepares large scale investment and portfolio datasets using statistical and quantitative techniques to support risk analytics and oversight.
Primary Responsibilities:
  • Partners with risk and portfolio managers to deliver quantitative, data-driven investment and portfolio risk solutions across liquid and illiquid alternative investment products.
  • Produces quantitative risk reporting and analytics to support monitoring of market, credit, liquidity, and derivatives risks for internal and regulatory purposes.
  • Applies quantitative analysis to evaluate portfolio risk characteristics, sensitivities, and profit and loss (PnL) drivers, including those arising from derivative instruments, in support of portfolio construction, hedging, and risk decision-making.
  • Develops and maintains models, processes, and workflows used for enterprise risk generation and validation.
  • Supports portfolio construction, validation, and reconciliation activities for market-traded and over-the-counter (OTC) instruments.
  • Ensures the accuracy, consistency, and reliability of portfolio data used in investment risk analytics and reporting.
  • Identifies investment risk management challenges and contributes to data-driven solutions in collaboration with stakeholders.

Education and Experience:
Bachelor's degree in Quantitative Finance, Finance, Computer Science, Accounting, Management, Financial Mathematics, Actuarial Science, Statistics, or a closely related field (or foreign education equivalent) and five (5) years of experience as a Principal Quantitative Developer (or closely related occupation) performing quantitative and analytical evaluation of portfolio and derivative risk models within an investment management or trading environment to support portfolio construction, and risk management decisions.
Or, alternatively, Master's degree in Quantitative Finance, Finance, Computer Science, Accounting, Management, Financial Mathematics, Actuarial Science, Statistics, or a closely related field (or foreign education equivalent) and three (3) years of experience as a Principal Quantitative Developer (or closely related occupation) performing quantitative and analytical evaluation of portfolio and derivative risk models within an investment management or trading environment to support portfolio construction, and risk management decisions.
Skills and Knowledge:
Candidate must also possess:
  • Demonstrated Expertise ("DE") validating and back testing portfolio and derivatives risk models against historical outcomes and benchmarks, using Python, R, and SQL; calibrating and validating model parameters and thresholds for market and derivatives risk measures, including expected shortfall, duration, leverage risk, liquidity risk, derivative exposure, option pricing models, and option sensitivity measures (Greeks), using Python and R; performing factor risk decomposition and non linear scenario generation, using MSCI RiskMetrics and MSCI Barra; producing Monte Carlo-based risk metrics and stress testing outputs for portfolios and trading strategies, using Python and MSCI RiskMetrics; and implementing model risk controls and periodic performance reviews through standardized validation scripts and documentation, using Python and R.
  • DE designing standardized and ad hoc risk reporting with risk attribution, performance analysis, and stress testing outputs, using Python and R; building interactive dashboards and visual analytics for portfolio and derivatives risk, using Python and Power BI; presenting reports to investment teams and senior leadership to communicate exposures, sensitivities, and PnL drivers, using Python and R; translating quantitative results into decision support insights for traders and risk managers, using Python notebooks and presentation templates; and enhancing reporting through automated validations and feedback cycles, using Python, SQL, and APIs.
  • DE extracting, cleansing, transforming, and validating large scale structured and semi structured financial data from internal databases and external sources, using SQL, Snowflake, Python, and APIs; integrating trading systems, and exchanging and clearing house data and Bloomberg feeds into curated datasets for research and risk reporting, using APIs, SQL, and Python; implementing automated data quality controls including missing data flagging, anomaly detection, and statistical validation, using Python and SQL; maintaining reproducible pipelines and metadata for lineage and auditability, using Snowflake and SQL; and preparing analytic ready datasets for downstream risk modeling, performance reporting, and visualization, using SQL, Snowflake, and Python.
  • DE designing and implementing automated workflows and batch processing for portfolio risk and performance analytics, derivative product validation, and trading system feature testing, using Python, SQL, Snowflake, Git, and APIs; optimizing code paths and data access using Python and database side SQL; and orchestrating end to end jobs to support quantitative analysis and operational readiness across internal and external systems through APIs and SQL database.

Salary: $155,000.00 to $166,000.00/Year
#PE1M2
#LI-DNI
Fidelity's Onsite Working Model
Fidelity is transitioning to a full-time onsite working model through a phased rollout across regions and roles. Currently, some roles and locations require 100% onsite presence, while others require less. Onsite expectations are likely to evolve as the rollout continues. This transition does not apply to fully remote roles.
Certifications:
Category:
Information Technology
Please be advised that Fidelity's business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.

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