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Associate Quantitative Risk Analyst Jobs in Houston, TX

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 ...

Anew Climate LLC

Global Risk Manager (6683)

Houston, TX · On-site

... analytics platforms, and quantitative methods. · Ability to communicate complex risk concepts clearly to both technical and non-technical audiences. · Demonstrated ability to influence senior ...

VoltaGrid

Senior Project Controls Manager

Houston, TX · On-site

Lead project-level risk identification and quantitative risk analysis across safety, cost, schedule, and regulatory exposure. * Oversee change management processes for engineering, construction, and ...

Energy transfer

Integrity Engineer

Houston, TX · On-site

Run quantitative risk model(s) for specific assets including coordination of data collection ... Ability to analyze data and apply critical thinking skills to generate options and solutions * The ...

ExxonMobil

Quant V&S Gas and Power

Spring, TX · On-site

... analysis and risk translation beyond the core Trading organization. What you will do * Provide fair ... Strong quantitative background (MSc/PhD preferred) with Front Office Gas & Power valuation ...

ExxonMobil

Quant V&S Gas and Power

Spring, TX

... analysis and risk translation beyond the core Trading organization. What you will do * Provide fair ... Strong quantitative background (MSc/PhD preferred) with Front Office Gas & Power valuation ...

ExxonMobil

Quant V&S Gas and Power

Spring, TX · On-site

... analysis and risk translation beyond the core Trading organization. What you will do * Provide fair ... Strong quantitative background (MSc/PhD preferred) with Front Office Gas & Power valuation ...

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All JobsAssociate Quantitative Risk Analyst JobsAssociate Quantitative Risk Analyst Jobs in Houston, TX

Associate Quantitative Risk Analyst information

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How much do associate quantitative risk analyst jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for associate quantitative risk analyst in Houston, TX is $38.66, according to ZipRecruiter salary data. Most workers in this role earn between $28.46 and $47.07 per hour, depending on experience, location, and employer.

What are some common challenges faced by Associate Quantitative Risk Analysts in their first year, and how can they overcome them?

In their first year, Associate Quantitative Risk Analysts often encounter challenges such as adapting to complex financial models, learning to interpret large datasets, and effectively communicating technical findings to non-technical stakeholders. Navigating regulatory requirements and understanding the company's risk management framework can also be demanding. To overcome these obstacles, new analysts should proactively seek mentorship, participate in team discussions, and leverage internal training resources to build both technical and soft skills. Regular collaboration with colleagues in risk, finance, and IT departments can also provide valuable insights and accelerate professional growth.

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

AspectAssociate Quantitative Risk AnalystCredit Risk Analyst
Required CredentialsBachelor's in finance, economics, or related field; often some familiarity with quantitative methodsBachelor's in finance, economics, or related field; certifications like CFA or FRM are common
Work EnvironmentFinancial institutions, risk management teams, quantitative departmentsBanking, lending institutions, credit departments
Employer & Industry UsageUsed in risk modeling, data analysis, and quantitative assessmentsFocuses on assessing creditworthiness and loan risk

The Associate Quantitative Risk Analyst primarily focuses on developing models and analyzing data to measure financial risks, often working with quantitative tools. In contrast, a Credit Risk Analyst concentrates on evaluating the creditworthiness of borrowers and managing credit risk. While both roles require similar educational backgrounds and work within financial institutions, their core responsibilities differ—one emphasizes quantitative modeling, the other credit assessment.

What are Associate Quantitative Risk Analysts?

Associate Quantitative Risk Analysts are entry- to mid-level professionals who help financial institutions and organizations assess and manage risk using mathematical models and statistical techniques. They analyze data to identify potential risks, develop risk management strategies, and support decision-making processes. Their work often involves using quantitative software, working with large datasets, and collaborating with other risk management and finance professionals. Typically, they have backgrounds in mathematics, statistics, finance, or related fields.

What are the key skills and qualifications needed to thrive as an Associate Quantitative Risk Analyst, and why are they important?

To thrive as an Associate Quantitative Risk Analyst, you need a strong background in mathematics, statistics, finance, and data analysis, typically supported by a relevant degree such as in finance, mathematics, or economics. Familiarity with statistical software (like R, SAS, or Python), financial modeling tools, and possibly certifications such as FRM or CFA is highly valuable. Strong analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting complex data and presenting findings. These competencies are essential for accurately assessing financial risks and supporting informed decision-making in risk management environments.
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Associate Quantitative Risk Analyst jobs near you

Quant Analyst - Commodities (Oil)

Verition Group LLC

Houston, TX

Other

Posted 2 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