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Assistant Machine Learning Quant Jobs in Live Oak, TX

... machine learning, and AI, and contribute to the team's knowledge sharing and continuous improvement culture. Qualifications : Required : • Master's degree in a quantitative field such as Computer ...

SWBC is seeking a talented individual who will contribute to the development of machine learning ... Contribute to the development and enhancement of Clara, SWBC's AI decision assistant, including ...

SWBC is seeking a talented individual who will contribute to the development of machine learning ... Contribute to the development and enhancement of Clara, SWBC's AI decision assistant, including ...

SWBC is seeking a talented individual who will contribute to the development of machine learning ... Contribute to the development and enhancement of Clara, SWBC's AI decision assistant, including ...

... machine learning models • Translate business problems into analytical solutions • Create ... quantitative analytical approaches • Ability to translate recommendations into communication ...

SWBC is seeking a talented individual to lead the development of critical machine learning and AI ... D. in a quantitative field such as Computer Science, Data Science, Statistics, Mathematics, or a ...

... assistant, and drive enterprise-wide analytics through forecasting models, segmentation analysis ... Design and implement machine learning and AI solutions, including predictive models, forecasting ...

Senior Data Scientist

San Antonio, TX · On-site

$140 - $210/hr

... assistant, and drive enterprise-wide analytics through forecasting models, segmentation analysis ... Design and implement machine learning and AI solutions, including predictive models, forecasting ...

... assistant, and drive enterprise-wide analytics through forecasting models, segmentation analysis ... Design and implement machine learning and AI solutions, including predictive models, forecasting ...

... assistant, and drive enterprise-wide analytics through forecasting models, segmentation analysis ... Design and implement machine learning and AI solutions, including predictive models, forecasting ...

Data Scientist

San Antonio, TX · On-site

$90 - $130/hr

SIMILAR CAREER TITLES Data Analyst, Machine Learning Engineer, AI Specialist, Statistician, Data Engineer, Business Intelligence Analyst, Quantitative Analyst, Research Scientist, Predictive ...

SIMILAR CAREER TITLES Data Analyst, Machine Learning Engineer, AI Specialist, Statistician, Data Engineer, Business Intelligence Analyst, Quantitative Analyst, Research Scientist, Predictive ...

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Assistant Machine Learning Quant information

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How much do assistant machine learning quant jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for assistant machine learning quant in Live Oak, TX is $15.59, according to ZipRecruiter salary data. Most workers in this role earn between $14.13 and $16.59 per hour, depending on experience, location, and employer.

What is an assistant machine learning quant?

Assistant Machine Learning Quants are entry-level professionals in quantitative finance who support senior quants by applying machine learning techniques to analyze financial data, build predictive models, and develop trading strategies. Their responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They work closely with quantitative researchers and traders to improve algorithmic trading systems and risk management processes. This role typically requires strong programming skills, a solid understanding of machine learning concepts, and familiarity with financial markets.

How does an assistant machine learning quant typically collaborate with senior quants and data scientists on projects?

As an Assistant Machine Learning Quant, you will often work closely with senior quantitative researchers and data scientists by supporting model development, data preprocessing, and feature engineering tasks. You may contribute to brainstorming sessions, implement prototypes, and assist in backtesting trading strategies or risk models. This collaborative environment provides valuable mentorship opportunities and exposure to best practices in quantitative analysis and machine learning within the finance industry. Effective communication and a willingness to learn from senior team members are key to success in this role.

What are the key skills and qualifications needed to thrive as an assistant machine learning quant, and why are they important?

To thrive as an Assistant Machine Learning Quant, you need strong quantitative skills, a background in statistics or mathematics, and typically a degree in a STEM field. Familiarity with programming languages such as Python or R, experience with machine learning frameworks, and knowledge of financial modeling tools are essential. Strong problem-solving abilities, attention to detail, and effective communication are standout soft skills in this role. These competencies enable accurate model development, efficient data analysis, and clear collaboration with team members in high-stakes financial environments.

What cities near Live Oak, TX are hiring for Assistant Machine Learning Quant jobs?

Cities near Live Oak, TX with the most Assistant Machine Learning Quant job openings:

Infographic showing various Assistant Machine Learning Quant job openings in Live Oak, TX as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $32,426 per year, or $15.6 per hour.

Machine Learning Engineer, Underwriting

FloatMe

San Antonio, TX • On-site

$140 - $190/hr

Other

Posted 24 days ago


Job description

We're hiring a Machine Learning Engineer to build and own the models behind our underwriting and decisioning systems at FloatMe. Our models determine who gets approved, how much, and under what terms — serving customers across a wide range of profiles. The challenges are real: maintaining calibration across diverse customer populations, designing features that generalize as the portfolio grows, and balancing approval rates against loss performance at every decision point. As a senior individual contributor on our ML team, you'll work across the full modeling lifecycle — from problem formulation and feature development to deployment, monitoring, and iteration in production. We move fast, test carefully, and hold our work to a high standard because the models we build determine real outcomes for real people. If you're excited to do rigorous, high-impact ML work at a fast-moving fintech, we'd love to hear from you.

What You’ll Do

  • You will be a senior individual contributor building and evolving the ML systems behind these products. You will work across the full modeling lifecycle: problem formulation, feature development, training, calibration, experimentation, deployment, monitoring, and iteration.

  • Build, evaluate, and maintain underwriting and decisioning models.

  • Design and evolve underwriting decision frameworks, including the modeling, automation, policy logic and amount assignment that manage exposure over time.

  • Design and run experiments to evaluate model performance, measure impact on approval rates and loss, margin and inform underwriting policy decisions.

  • Develop deep understanding of consumer behavior, repayment dynamics, and portfolio structure, and use that to inform model design and decision logic.

  • Contribute analysis and perspective that inform portfolio-level decisions, including explaining model behavior, tradeoffs, and uncertainty to senior technical and business leaders.

  • Develop and maintain the key portfolio KPIs and inventory of periodic analysis to continuously identify risk and growth opportunities

  • Collaborate with Product, Engineering, Legal, Compliance, and Operations to ensure underwriting systems reflect business goals and regulatory expectations.

Technologies We Use and Teach:

  • Python (NumPy, Pandas, scikit-learn, PyTorch, XGBoost, LightGBM)

  • AI development tools as core infrastructure: Claude Code, Cursor, Copilot

  • ML flow for experiment tracking and model registry

  • Internal feature store and model hosting platform

  • SQL / Snowflake

  • GitHub

  • AWS

  • BI tools (Looker/PowerBI/Tableau)

Who You Are

  • A Master degree in a quantitative field (e.g., Mathematics, Statistics, Physics, Computer Science, Operation Research). A PhD degree is strongly welcomed.

  • 5+ years applying AI, machine learning, or statistical modeling in decisioning contexts such as credit, risk, fraud, recommendations, or similar domains.

  • Experience with probabilistic models and decision systems, including calibration, score transformations, and interpretation of model outputs.

  • Strong experimentation skills: you know how to design holdouts, measure lift, and evaluate models beyond aggregate metrics.

  • Experience with model monitoring, degradation detection, and retraining strategies in production systems.

  • Deep knowledge of underwriting using bank & cashflow analysis, bureau & alternative data etc. with a focus on unsecured credit risk

  • Experience explaining modeling concepts, results, and limitations to senior stakeholders and cross-functional partners.

Bonus Points

  • Fintech background

  • Consumer finance experience (non-large bank environment)

  • Advanced modeling techniques

  • Background in small to medium sized companies

FloatMe is proud to be an equal opportunity employer. FloatMe provides equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws, and prohibits discrimination and harassment of any type.

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