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Quantitative Model Developer Jobs (NOW HIRING)

... programming skills in SAS, Python, SQL, or similar Understanding of AML regulations Ability to ... model behavior to non-technical stakeholders Strong organizational, analytical, and project ...

Sr. Quantitative Model Analyst General Summary: Independently leads and assists activities related ... Proficiency in programming languages such as Python, R, or MATLAB, with experience in data ...

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Quantitative Model Developer information

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How much do quantitative model developer jobs pay per year?

As of Sep 10, 2026, the average yearly pay for quantitative model developer in the United States is $169,729.00, according to ZipRecruiter salary data. Most workers in this role earn between $134,500.00 and $199,000.00 per year, depending on experience, location, and employer.

What does a quantitative model developer do?

A Quantitative Model Developer designs, implements, and maintains mathematical models used in finance, banking, or other industries to analyze data and support decision-making. They use programming languages, statistical techniques, and financial theory to develop models for tasks such as risk assessment, pricing, or forecasting. These professionals work closely with traders, analysts, and other stakeholders to ensure the models are accurate, efficient, and aligned with business goals.

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

To excel as a Quantitative Model Developer, you need strong mathematical and statistical skills, proficiency in programming languages like Python, R, or C++, and typically a degree in mathematics, statistics, computer science, or a related field. Experience with modeling frameworks, data analysis tools, and familiarity with quantitative finance platforms such as MATLAB or QuantLib are commonly required. Critical thinking, attention to detail, and effective communication are important soft skills for interpreting complex data and collaborating with cross-functional teams. These abilities are essential for developing accurate, reliable models that inform financial decision-making and risk management.

How does a quantitative model developer typically collaborate with other teams within a financial institution?

Quantitative Model Developers frequently work alongside risk management, trading, and IT departments to ensure that financial models are both robust and aligned with business objectives. They often translate complex mathematical concepts for stakeholders, assist in model implementation, and respond to feedback or changing requirements. Collaboration is key, as they must ensure models are technically sound, regulatory compliant, and seamlessly integrated into production systems. Regular communication and interdisciplinary teamwork are essential for resolving challenges and delivering effective solutions.

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

AspectQuantitative Model DeveloperQuantitative Analyst
Primary FocusDesigning, developing, and implementing quantitative modelsAnalyzing data to inform trading, investment, or risk decisions
Skills & CertificationsProgramming (Python, C++, R), quantitative finance, model developmentData analysis, statistical skills, financial knowledge
Work EnvironmentQuant teams in finance firms, hedge funds, banksResearch teams, trading desks, investment firms
Common UsageBuilding models used in trading algorithms and risk managementInterpreting data to support investment strategies

While both roles require quantitative skills and finance knowledge, Quantitative Model Developers focus on creating and coding models, whereas Quantitative Analysts analyze data to guide decisions. The roles often overlap but differ mainly in their core responsibilities and technical focus.

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Cities with the most Quantitative Model Developer job openings:

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Infographic showing various Quantitative Model Developer job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 83% Full Time, 14% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $169,729 per year, or $81.6 per hour.

Cross‑Margin Quantitative Model Developer

Charlotte, NC • On-site

Strategic Staffing Solutions
Professional, Scientific, and Technical Services • 201 - 500 employees

Other

Posted 7 days ago


Job description

JOB-247878 Cross‑Margin Quantitative Model Developer - 233775-1

Client: Wells Fargo

Location: Charlotte, NC 28202


Schedule: Hybrid – 3 days per week in-office


Duration: 12 months with potential to extend


Interview: 30 min MS Teams call, possible 2nd round


No Corp to Corp.



Job Description: Cross‑Margin Quantitative Model Developer

Primary Focus: Vendor-model development (Hanweck) for equity option pricing, volatility surface, and stressed or shocked-scenario P&L. The go live for options (which this risk model will support) is next April 2027.


Team: Contingent Solutions – Counterparty Credit Risk Modeling


Overview

We are seeking a highly analytical Quantitative Model Developer with strong Python engineering skills and deep familiarity with cross‑margining concepts within prime brokerage and capital markets. This role focuses on enhancing and maintaining counterparty credit risk models—not pricing or market risk models—with an emphasis on mathematical rigor, cross‑product methodology development, and hands-on coding.

The ideal candidate has a strong mathematical foundation, the ability to derive formulas, identify methodological gaps, and improve model implementations. You will work closely with junior team members, business partners, model owners, technology stakeholders, and project management groups.

Because cross‑margin exposure plays a significant and high-impact role in CIB markets, this position requires a strong sense of urgency and responsiveness to ad hoc model requests.


Key Responsibilities

  • Modeling & Quantitative Analysis
  • Develop, enhance, and maintain counterparty credit risk models related to cross‑margin methodologies.
  • Derive analytical formulas, validate assumptions, and identify gaps in existing implementations.
  • Improve or replace outdated models using modern stochastic and capital markets modeling techniques.
  • Support modeling across a range of complex financial products, including:


  • Equity swaps
  • Metals
  • Energy derivatives
  • Convertible bonds


Technical Development

  • Lead the build‑out and integration of Python-based quantitative libraries to support model development and validation activities.
  • Produce robust prototype models and partner with technology teams to transition them into production.
  • Utilize generative AI development tools (e.g., Copilot) to increase coding efficiency and automation.
  • Collaborate on database queries using strong SQL expertise.


Cross‑Functional Collaboration

  • Communicate clearly with model owners, business partners, technology teams, auditors, and project managers.
  • Help translate business requirements into quant/model specifications and documentation.
  • Provide coaching and technical guidance to junior team members on both modeling and cross‑margin concepts.


Operational Readiness

  • Respond quickly to urgent model requests driven by high-impact cross‑margin exposures in the CIB business.
  • Ensure timely delivery of model enhancements, documentation, and validations.


Required Technical Skills

  • Python (expert level) – ability to build, structure, and maintain quant libraries.
  • Experience using AI-assisted coding tools (Copilot or similar).
  • SQL expertise – ability to query and manipulate large datasets.
  • Strong numerical skills and experience with stochastic modeling and capital markets models.


Required Quantitative Skills

  • Ability to derive mathematical formulas and implement them programmatically.
  • Strong understanding of cross‑margining concepts in prime brokerage or derivatives clearing.
  • Ability to identify and correct model gaps, inconsistencies, or legacy issues.
  • Solid foundation in probability, statistics, and stochastic processes.


Skill Weighting

  • Cross‑margin expertise: ~50%
  • Mathematics/modeling: ~30%
  • Coding (Python/SQL): ~20%


Preferred Qualifications

  • Experience in prime brokerage or margin methodology design.
  • Prior work with counterparty credit exposure models (e.g., PFE, EE, EAD).
  • Familiarity with equities, commodities, energy, and structured derivative products.
  • Candidates located in Charlotte are strongly preferred; two existing team members are based here.