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Quant Analytics Jobs in Houston, TX (NOW HIRING)

Expand Energy

Quantitative Risk Analyst

Spring, TX · On-site

Job Duties & Responsibilities 1) Quantitative Modeling, Valuation, and Analytics * Develop and maintain quantitative models for valuation, exposure measurement, and risk assessment across physical ...

ExxonMobil

Quantitative Analyst, V&S LNG

Spring, TX

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Proficiency in Python and experience with quantitative analytics libraries, optimization frameworks ... and data science toolsets. * Experience working with large and complex datasets to generate ...

ExxonMobil

Quantitative Analyst, V&S LNG

Spring, TX

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Proficiency in Python and experience with quantitative analytics libraries, optimization frameworks ... and data science toolsets. * Experience working with large and complex datasets to generate ...

ExxonMobil

Quantitative Analyst, V&S LNG

Spring, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Proficiency in Python and experience with quantitative analytics libraries, optimization frameworks ... and data science toolsets. * Experience working with large and complex datasets to generate ...

Expand Energy

Quantitative Risk Analyst

Spring, TX

Job Duties & Responsibilities 1) Quantitative Modeling, Valuation, and Analytics * Develop and maintain quantitative models for valuation, exposure measurement, and risk assessment across physical ...

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All JobsQuant Analytics JobsQuant Analytics Jobs in Houston, TX

Quant Analytics information

See Houston, TX salary details

$50.1K

$113.8K

$187.7K

How much do quant analytics jobs pay per year?

As of Aug 13, 2026, the average yearly pay for quant analytics in Houston, TX is $113,800.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,000.00 and $145,600.00 per year, depending on experience, location, and employer.

What is the difference between Quant Analytics vs Data Analyst?

AspectQuant AnalyticsData Analyst
Required CredentialsDegree in finance, mathematics, or related fields; often requires programming skillsDegree in statistics, business, or related fields; may require basic programming knowledge
Work EnvironmentFinancial firms, hedge funds, investment banksCorporate, marketing, healthcare, and other industries
Job FocusDeveloping complex models for trading and risk managementInterpreting data to inform business decisions and reporting

Quant Analytics professionals focus on building advanced financial models and algorithms primarily in finance and trading environments. Data Analysts interpret and visualize data to support business strategies across various industries. While both roles involve data handling, Quant Analytics emphasizes quantitative modeling and programming, whereas Data Analysts focus on data interpretation and reporting.

What are the key skills and qualifications needed to thrive as a quant analytics professional?

To thrive in Quant Analytics, you need strong quantitative skills, advanced knowledge of mathematics and statistics, and often a degree in fields like mathematics, physics, engineering, or finance. Familiarity with programming languages such as Python, R, or MATLAB, as well as experience with data analysis tools and financial modeling software, is typically required. Analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting complex data and conveying insights to stakeholders. These skills and qualities are vital for developing robust quantitative models that support informed decision-making in fast-paced financial environments.

What is a quant analytics professional?

Quant Analytics, short for quantitative analytics, refers to the use of mathematical models, statistical methods, and computational techniques to analyze financial data and inform investment decisions. Professionals in this field, known as quantitative analysts or 'quants,' develop and implement algorithms for risk management, pricing, trading strategies, and portfolio management. Quant Analytics is widely used in banks, hedge funds, and investment firms to gain insights from large data sets and optimize financial performance. The role typically requires strong skills in mathematics, programming, and finance.

What does a quant analytics do?

A quant analyst, or quantitative analyst, develops mathematical models and uses statistical techniques to analyze financial data and inform investment decisions. They often work with programming languages like Python or R and tools such as Excel or specialized software to identify trends, assess risks, and optimize trading strategies.

How do quant analytics professionals typically collaborate with other teams within a financial institution?

Quant Analytics professionals often work closely with traders, risk managers, and software engineers to develop, implement, and refine quantitative models. They translate complex data into actionable insights, which may influence trading strategies or risk assessment. Effective communication and teamwork are essential, as quants must present their findings in a way that is understandable and useful to non-technical stakeholders. Collaboration is usually facilitated through regular meetings, code reviews, and joint problem-solving sessions.
What cities near Houston, TX are hiring for Quant Analytics jobs? Cities near Houston, TX with the most Quant Analytics job openings:
Quant Analytics jobs near you
Infographic showing various Quant Analytics job openings in Houston, TX as of July 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 100% In-person job distribution, with an average salary of $113,800 per year, or $54.7 per hour.

Commodities Quant Analyst

Verition Group LLC

Houston, TX • On-site

Full-time

Posted 21 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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