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Credit Quant Jobs in Texas (NOW HIRING)

GM Financial

Risk Credit Policy Analyst II

Irving, TX · Hybrid

Demonstrated quantitative skills * Acute attention to detail * Effective written and verbal ... Risk Credit Policy Analyst II is responsible for analyzing credit risk exposure related to consumer ...

USAA

Lead Analyst, Credit Risk Strategy

Plano, TX · On-site

You will use quantitative methods to identify credit risk, develop and deliver credit strategies, and monitor credit performance for consumer credit portfolios to optimize profitable growth within ...

New

USAA

Lead Analyst, Credit Risk Strategy

Plano, TX

You will use quantitative methods to identify credit risk, develop and deliver credit strategies, and monitor credit performance for consumer credit portfolios to optimize profitable growth within ...

New

USAA

Lead Analyst, Credit Risk Strategy

Plano, TX · On-site

You will use quantitative methods to identify credit risk, develop and deliver credit strategies, and monitor credit performance for consumer credit portfolios to optimize profitable growth within ...

New

USAA

Lead Analyst, Credit Risk Strategy

San Antonio, TX · On-site

You will use quantitative methods to identify credit risk, develop and deliver credit strategies, and monitor credit performance for consumer credit portfolios to optimize profitable growth within ...

New

T-Mobile

Sr Analyst, Credit Risk Mgmt

Frisco, TX · On-site

$84K - $152K/yr

Perform sophisticated qualitative and quantitative analysis of credit polices to ensure financial goals are being attained * Develop predictive financial and analytical models using the appropriate ...

Regional Finance

Manager Credit Risk

Plano, TX

Job purpose The Manager, Credit Risk is responsible for performance analysis, operational reporting ... Quantitative analysis of custom score models including , validation, ongoing- performance ...

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Credit Quant information

What is the difference between Credit Quant vs Credit Analyst?

AspectCredit QuantCredit Analyst
Required CredentialsAdvanced degrees (e.g., Master’s, PhD), quantitative certifications (e.g., CFA, FRM)Bachelor’s degree often sufficient, finance or economics background
Work EnvironmentQuantitative teams, research-focused, often in investment banks or hedge fundsCredit departments, risk management, lending institutions
Industry UsageUsed for modeling, risk assessment, and algorithm developmentUsed for credit evaluation, client assessment, and loan decisions

While Credit Quant professionals focus on developing complex models and quantitative analysis for risk and pricing, Credit Analysts primarily evaluate creditworthiness of clients and make lending decisions. Both roles are essential in finance but differ in their focus, skills, and daily tasks.

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Credit Quant jobs near you

Commodities Quant Analyst

Verition Group LLC

Houston, TX • On-site

Full-time

Posted 17 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 a leading multi-strategy hedge fund, is seeking a Quantitative Analyst to join a commodities-focused investment pod in Houston. This is a highly research-oriented role working directly alongside an experienced Portfolio Manager to develop differentiated investment signals using alternative data and quantitative research techniques. The successful candidate will combine a strong foundation in statistics, financial modeling, and Python with a genuine curiosity for uncovering new sources of alpha. Rather than focusing on software engineering, this individual will spend their time researching markets, identifying unique datasets, testing hypotheses, and developing predictive signals that can be incorporated directly into the investment process.
A significant portion of the role will involve sourcing, analyzing, and modeling alternative datasets related to global commodity markets. This includes working with data such as crude oil vessel tracking (AIS), shipping and freight activity, pipeline flows, refinery operations, storage and inventory data, weather, satellite imagery, and other non-traditional datasets. The objective is to transform raw information into robust, statistically validated signals that provide a measurable investment edge.
Responsibilities:
  • Developing financial time series models and predictive forecasting techniques across energy and commodity markets.
  • Researching, evaluating, and incorporating alternative datasets into the investment process.
  • Designing, testing, and validating alpha signals through rigorous statistical analysis and backtesting.
  • Building research pipelines to clean, organize, and analyze large structured and unstructured datasets.
  • Leveraging AI and machine learning techniques to improve feature engineering, accelerate research, and identify differentiated investment opportunities.
  • Collaborating with the Portfolio Manager to rapidly prototype new ideas and continuously refine investment models as market dynamics evolve.

Qualifications:
  • Python and the broader scientific computing ecosystem, including libraries such as Pandas, NumPy, SciPy, and scikit-learn.
  • Financial time series analysis, statistical modeling, feature engineering, and hypothesis testing.
  • Backtesting frameworks, predictive modeling, and signal evaluation.
  • Machine learning techniques and modern AI tools, including large language models, to accelerate quantitative research.
  • SQL, cloud-based data platforms, and experience working with large-scale structured and unstructured datasets.

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