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Quantitative Risk Analyst Jobs in Houston, TX (NOW HIRING)

Optimus

Middle Office Analyst

Houston, TX · On-site

Deliver daily analysis and explanations of key risk metrics and any limit breaches. * Coordinate ... quantitative discipline. * Strong understanding of risk management methodologies and valuation ...

Venturegloballng

Analyst, Pricing Risk

Houston, TX

Analyst, Pricing Risk Located: Houston Summary We are seeking an Analyst, Pricing Risk to join our ... highly quantitative field. Venture Global LNG is an Equal Opportunity Employer. We do not ...

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Quantitative Risk Analyst information

See Houston, TX salary details

$54K

$127.8K

$229.2K

How much do quantitative risk analyst jobs pay per year?

As of Aug 10, 2026, the average yearly pay for quantitative risk analyst in Houston, TX is $127,849.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,500.00 and $138,900.00 per year, depending on experience, location, and employer.

What are some common challenges a quantitative risk analyst faces when integrating new data sources into risk models?

Quantitative Risk Analysts often encounter challenges related to data quality, consistency, and compatibility when integrating new data sources into risk models. Ensuring that the data is accurate, timely, and relevant requires rigorous validation and sometimes complex data cleaning processes. Additionally, analysts must adapt existing risk models to accommodate new variables, which may involve re-calibrating parameters or even restructuring parts of the model. Effective collaboration with IT and data engineering teams is essential to streamline data integration and maintain model reliability.

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

To thrive as a Quantitative Risk Analyst, you need strong analytical and mathematical skills, experience with statistical modeling, and typically a degree in finance, mathematics, statistics, or a related field. Proficiency in programming languages such as Python, R, or MATLAB, and familiarity with risk management systems and financial databases are important technical requirements. Attention to detail, problem-solving abilities, and effective communication are vital soft skills for explaining complex analyses to stakeholders. These skills are crucial for accurately identifying, measuring, and mitigating financial risks in dynamic market environments.

What is the difference between Quantitative Risk Analyst vs Credit Risk Analyst?

AspectQuantitative Risk AnalystCredit Risk Analyst
Required CredentialsDegree in finance, economics, or mathematics; certifications like FRM or CFADegree in finance, economics, or related; certifications like FRM or CFA often preferred
Work EnvironmentFinancial institutions, investment firms, risk management departmentsBanks, lending institutions, credit agencies
Employer & Industry UsageUsed across finance sectors for risk modeling and analysisPrimarily in banking and lending for assessing creditworthiness
Comparison Search IntentUnderstanding differences in risk analysis rolesDistinguishing credit-specific risk roles from broader risk analysis

While both roles involve risk assessment and require similar credentials, a Quantitative Risk Analyst focuses on modeling and analyzing various financial risks using quantitative methods across multiple risk types. In contrast, a Credit Risk Analyst specializes in evaluating creditworthiness and managing credit risk specifically within lending and banking sectors.

What is a quantitative risk analyst?

A Quantitative Risk Analyst is a professional who uses mathematical models, statistical techniques, and data analysis to assess and manage financial risks within an organization. They typically evaluate potential losses from market movements, credit defaults, or operational failures and help develop strategies to mitigate those risks. Their work is crucial in industries such as banking, investment, insurance, and asset management, where understanding and controlling risk is essential for financial stability and compliance. Quantitative Risk Analysts often work with complex financial instruments and large datasets, requiring strong analytical and programming skills.
What are the most commonly searched types of Quantitative Risk Analyst jobs in Houston, TX? The most popular types of Quantitative Risk Analyst jobs in Houston, TX are:
What are popular job titles related to Quantitative Risk Analyst jobs in Houston, TX? For Quantitative Risk Analyst jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Quantitative Risk Analyst jobs in Houston, TX look for? The top searched job categories for Quantitative Risk Analyst jobs in Houston, TX are:
What cities near Houston, TX are hiring for Quantitative Risk Analyst jobs? Cities near Houston, TX with the most Quantitative Risk Analyst job openings:
Quantitative Risk Analyst jobs near you
Infographic showing various Quantitative Risk Analyst job openings in Houston, TX as of August 2026, with employment types broken down into 1% As Needed, 91% Full Time, 6% Part Time, and 2% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $127,849 per year, or $61.5 per hour.

Quant Analyst - Commodities (Oil)

Verition Group LLC

Houston, TX • On-site

Full-time

Re-posted 4 days ago

Job description

Verition Fund Management LLC ("Verition") is a multi-strategy, multi-manager hedge fund founded in 2008. Verition focuses on global investment strategies including Global Credit, Global Convertible, Volatility & Capital Structure Arbitrage, Event-Driven Investing, Equity Long/Short & Capital Markets Trading, and Global Quantitative Trading.
We are seeking a quantitative researcher to join a world class commodities trading team. This role is focused on building and enhancing data, analytics, and quantitative tools that support discretionary trading decisions. The ideal candidate combines strong coding and statistical foundations with practical experience applying machine learning and early-stage AI techniques to real-world problems. Prior exposure to crude oil markets is strongly preferred.
Responsibilities:
  • Develop and maintain Python-based research, analytics, and data pipelines to support trading and market analysis.
  • Design and manage databases and structured data workflows, including SQL-based querying and cloud-hosted data solutions.
  • Build dashboards and interactive tools (e.g., Streamlit) to visualize market data, signals, and risk metrics for the trading desk.
  • Apply statistical techniques and machine learning methods to analyze historical and real-time market data.
  • Contribute to the development and refinement of quantitative signals and core strategies used in commodities trading.
  • Explore and implement practical AI applications, including NLP and neural network-based approaches, where relevant to the trading process.
  • Work closely with the trader to prioritize projects, translate trading intuition into quantitative frameworks, and iterate quickly.

Qualifications:
  • Python (minimum 3+ years of professional experience; required) for data analysis.
  • Prior experience in commodities markets, particularly oil, is strongly preferred.
  • Git / version control (required).
  • Solid applied statistics (e.g., linear and logistic regression, autocorrelation, time-series concepts).
  • Machine learning fundamentals and common tools (e.g., SVMs, model evaluation best practices).
  • SQL and relational databases (e.g., Snowflake).
  • Dashboarding and data visualization (ideally Streamlit).
  • Cloud platforms (AWS, Azure, or similar).
  • Experience working with large, noisy, real-world datasets.
  • Strong conceptual understanding of NLP and neural networks.
  • Motivated to build tools and research that directly impact P&L.

Apply