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Derivative Pricing Quant Jobs (NOW HIRING)

Roth

Derivatives Sales Trader

New York, NY · On-site

... derivative desks, hedge funds, and other sophisticated counterparties. Skills and Attributes: * Strong quantitative skills with fluency in options pricing, volatility, and risk (Greeks) concepts

Trading Interview

$175K - $250K/yr

... quant team to further enhance the options desk. Responsibilities * Conceptualize and implement cutting-edge derivative pricing models for single-asset derivatives, as well as pricing models for ...

Trading Interview

$175K - $250K/yr

... quant team to further enhance the options desk. Responsibilities * Conceptualize and implement cutting-edge derivative pricing models for single-asset derivatives, as well as pricing models for ...

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How much do derivative pricing quant jobs pay per year?

As of Sep 11, 2026, the average yearly pay for derivative pricing quant in the United States is $92,983.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,000.00 and $118,500.00 per year, depending on experience, location, and employer.

What is a derivative pricing quant?

A Derivative Pricing Quant is a quantitative analyst who specializes in developing mathematical models and computational tools to determine the fair value of derivative financial products, such as options, futures, and swaps. This role involves using advanced mathematical techniques, programming, and financial theory to analyze market data and assess risks. Derivative Pricing Quants often collaborate with traders, risk managers, and IT professionals to ensure accurate pricing and effective risk management of complex financial instruments. Strong skills in mathematics, programming (such as Python or C++), and finance are essential for this position.

What are the key skills and qualifications needed to thrive as a derivative pricing quant?

To thrive as a Derivative Pricing Quant, you need advanced quantitative skills, a solid background in mathematics or financial engineering, and often a graduate degree in a quantitative field. Proficiency in programming languages like Python, C++, and familiarity with pricing libraries and risk management systems are typically required. Strong analytical thinking, attention to detail, and the ability to communicate complex ideas clearly are crucial soft skills. These abilities are important because they enable accurate pricing, effective risk assessment, and clear communication of technical findings to stakeholders in fast-moving financial markets.

What are some common challenges faced by a derivative pricing quant in their day-to-day work?

Derivative Pricing Quants frequently encounter challenges such as managing model risk, ensuring computational efficiency, and staying current with evolving financial regulations. The role often involves working with large, complex datasets and implementing advanced mathematical models under tight deadlines. Collaboration with traders, risk managers, and software engineers is essential to deliver robust pricing solutions and to adapt models to real-time market conditions. Addressing discrepancies between theoretical models and actual market behavior is a core part of the job, requiring both analytical rigor and creative problem-solving.

What are popular job titles related to Derivative Pricing Quant jobs?

For Derivative Pricing Quant jobs, the most frequently searched job titles are:

Infographic showing various Derivative Pricing Quant job openings in the United States as of September 2026, with employment types broken down into 80% Full Time, 18% Part Time, 1% Temporary, and 1% Contract. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution, with an average salary of $92,983 per year, or $44.7 per hour.

Quantitative Analytics Specialist (Markets / Derivatives)

Charlotte, NC • On-site

1 point system
IT Services • 51 - 200 employees
Learn more about 1 point systemexternal

Contractor

Re-posted 27 days ago

Job description

Notes--Capital markets, derivatives products knowledge is most important.

Quantitative Analytics Specialist (Markets / Derivatives)

Role Overview (Executive Summary)
We are seeking a Quantitative Analytics Specialist with strong experience in developing and implementing quantitative models that support derivatives pricing, P&L attribution, and risk analytics within a Corporate & Investment Banking environment.
The role requires hands-on expertise in building and integrating production-grade pricing models, P&L explain frameworks, and risk analytics, with a particular focus on equity derivatives (listed and OTC). The successful candidate will combine deep quantitative modeling skills with a strong understanding of how trade, market, and risk data interact to drive valuation, P&L, and capital markets reporting outcomes.
This position operates at the intersection of quantitative modeling, capital markets products, and enterprise data, partnering closely with Front Office, Risk, Finance, and Technology teams to deliver scalable, consistent, and high-quality analytics across the firm.

1. Capital Markets Data Models & Trade Analytics (Core Requirement)
Desired Experience

  • Deep expertise in equity derivatives and capital markets trade data models (listed and OTC), including:
    • Trade structure, payoffs, and lifecycle events (execution ? modification ? settlement)
    • Position models and trade-level vs aggregated representations
  • Strong experience with canonical / common domain models:
    • Mapping source trade payloads (FIX, JSON, XML) into standardized representations
    • Ensuring consistent trade modeling across Front Office, Risk, and Finance
  • Deep understanding of data required for pricing, P&L, and risk, including:
    • Trade economics and valuation inputs (curves, vol surfaces, dividends, correlations)
    • Market data, reference data (instruments, counterparties), and collateral data
  • Proven ability to design and validate cross-dataset joins and data lineage:
    • Linking trades, positions, and market data
    • Ensuring consistency across pricing, P&L attribution, and risk outputs
  • Strong knowledge of capital markets data flows:
    • Front Office ? Risk ? Finance ? Regulatory / Reporting
    • Multi-source integration and enterprise data distribution patterns

Key Responsibilities

  • Define and standardize trade and position data models across pricing, risk, and finance platforms
  • Design and own data integration across trade, market, reference, and collateral datasets
  • Implement and validate cross-dataset joins supporting pricing, P&L, and risk analytics
  • Ensure data quality, consistency, and completeness for all valuation and risk inputs
  • Establish data lineage and traceability to support audit, regulatory, and model validation needs
  • Enable scalable data distribution (“source once, distribute many”) across enterprise consumers

2. Quantitative Modeling, P&L, and Risk Analytics
Desired Experience

  • Proven experience building and implementing derivatives pricing models, with strong focus on equity derivatives (listed and OTC)
  • Deep understanding of pricing methodologies (stochastic modeling, Monte Carlo, volatility modeling) and model calibration to market data
  • Strong experience with P&L attribution (PLA) and understanding how pricing models, trade data, and market data drive daily P&L
  • Experience explaining P&L across sensitivities, market movements, and model factors
  • Hands-on experience with market risk analytics, including sensitivities, stress testing, and risk factor modeling across asset classes (equity, rates, FX, credit)
  • Experience aggregating exposures across portfolios and ensuring consistency across Front Office, Risk, and Finance
  • Familiarity with model validation, governance, and regulatory-driven analytics

Preferred Qualifications

  • Strong knowledge of cross-asset derivatives (Equity, FX, Rates, Credit) and associated risk factors
  • Experience working with enterprise risk and valuation platforms supporting cross-asset aggregation
  • Familiarity with regulatory frameworks (e.g., FRTB, P&L attribution requirements)
  • Experience operating in large-scale data and analytics environments
  • 7+ years of experience in Capital Markets or Investment Banking, with significant exposure to derivatives trading and quantitative analytics