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Python Quant Jobs in Houston, TX (NOW HIRING)

ComboCurve, Inc.

Senior Data Engineer, Python

Houston, TX · On-site +1

$109K - $131K/yr

This role requires a unique combination of deep Python expertise, mastery of modern data processing ... Quantitative Analysis & Optimization * Collaborate with reservoir and operations teams to translate ...

MD Anderson

Senior Commercial Analyst

Houston, TX · On-site

$84K - $111K/yr

Programming proficiency, Python * Experience with MS SQL, VBA * Excellent quantitative and analytical skills JERA Americas does not accept unsolicited resumes from third party recruiters or ...

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How much do python quant jobs pay per hour?

As of Jun 7, 2026, the average hourly pay for python quant in Houston, TX is $55.98, according to ZipRecruiter salary data. Most workers in this role earn between $46.15 and $63.61 per hour, depending on experience, location, and employer.

What are some typical challenges faced by Python Quants in the financial industry?

Python Quants often face challenges related to sourcing, cleaning, and managing large sets of complex financial data, as well as ensuring their models remain robust under rapidly-changing market conditions. Navigating tight deadlines while maintaining code quality and accuracy is a common aspect of the job. Additionally, the need to explain complex quantitative concepts to non-technical stakeholders, such as portfolio managers or traders, requires strong communication skills. Overcoming these challenges helps Python Quants deliver real, actionable insights and contribute effectively to investment strategies.

What are the key skills and qualifications needed to thrive in the Python Quant position, and why are they important?

To thrive as a Python Quant, you need strong quantitative skills, proficiency in Python programming, and a solid foundation in mathematics, statistics, or financial engineering, typically supported by an advanced degree. Familiarity with scientific computing libraries (e.g., NumPy, pandas, SciPy), version control systems like Git, and experience with financial data platforms are essential. Analytical thinking, attention to detail, and effective communication enable collaboration with traders and researchers. These skills and tools are crucial for developing, testing, and implementing robust quantitative models in dynamic financial environments.

What is a Python Quant job?

A Python Quant (Quantitative Analyst) job involves using Python to analyze financial data, develop trading algorithms, and build risk models. Python Quants work in hedge funds, investment banks, or proprietary trading firms, leveraging data science, machine learning, and statistical techniques. They write and optimize code for backtesting strategies, automating trades, and processing large datasets. Strong programming, mathematical, and financial knowledge are essential for success in this role.

What are the most commonly searched types of Python Quant jobs in Houston, TX? The most popular types of Python Quant jobs in Houston, TX are:
What are popular job titles related to Python Quant jobs in Houston, TX? For Python Quant jobs in Houston, TX, the most frequently searched job titles are:
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Python Quant jobs near you
Infographic showing various Python Quant job openings in Houston, TX as of May 2026, with employment types broken down into 100% Full Time. Highlights an 82% Physical, 7% Hybrid, and 11% Remote job distribution, with an average salary of $116,442 per year, or $56 per hour.
Senior Data Engineer, Python

Senior Data Engineer, Python

ComboCurve, Inc.

Houston, TX • On-site, Remote

$109K - $131K/yr

Full-time

Posted 27 days ago

Job description

ComboCurve is a industry leading cloud-based software solution for A&D, reservoir management, and forecasting in the energy sector. Our platform empowers professionals to evaluate assets, optimize workflows, and manage reserves efficiently, all in one integrated environment.
By streamlining data integration and enhancing collaboration, we help operators, engineers, and financial teams make informed decisions faster. Trusted by top energy companies, ComboCurve delivers real-time analytics and exceptional user support, with a world-class customer experience team that responds to inquiries in under 5 minutes.
We are seeking a highly analytical and experienced Senior Data Engineer to help optimize production forecasting and operations scheduling within the petroleum engineering domain. You'll bridge the gap between complex mathematical models (reservoir dynamics, optimization, logistics) and robust, cloud-scale data systems.
This role requires a unique combination of deep Python expertise, mastery of modern data processing and API frameworks, and a strong foundational understanding of mathematics, reasoning, and petroleum engineering principles.
Responsibilities
Data Architecture & Engineering
  • Design, build, and maintain scalable data pipelines for ingesting, transforming, and validating time-series data related to well performance, sensor readings, and operational logs.
  • Develop robust, high-performance data models using PyArrow and Pandas for efficient analysis and transfer.
  • Implement data quality and schema validation using Pydantic to ensure data integrity across all stages of the pipeline.
  • Manage and optimize data storage and retrieval in MongoDB, and integrate with cloud-native platforms like GCP BigQuery or Snowflake where applicable.

API & Application Development
  • Build, deploy, and maintain high-performance asynchronous microservices and prototypes using FastAPI or Flask to serve complex optimization and scheduling model predictions.
  • Use Postman for testing, documenting, and automating API workflows.
  • Containerize and orchestrate applications using Docker and manage deployment on Google Cloud Platform (GCP).

Quantitative Analysis & Optimization
  • Collaborate with reservoir and operations teams to translate complex scheduling and logistics problems into mathematical models (e.g., linear programming, resource allocation).
  • Implement numerical routines and simulations efficiently using NumPy for use in production environments.
  • Apply strong logical and analytical reasoning to debug, validate, and interpret the outputs of operational scheduling algorithms.

Requirements
  • Education: Bachelor's or Master's degree in Petroleum Engineering, Computer Science, Mathematics, Operations Research, or related quantitative field, or equivalent experience.
  • Quantitative Strength: Proven ability to work with mathematical modeling, optimization, and time-series analysis, including:

o Linear and Mixed-Integer Programming
o Probability and Statistics
o Algorithmic Complexity and Performance Reasoning
  • Collaborative mindset - experience working closely with data scientists, product owners, and domain experts to deliver production-ready systems.

Preferred Qualifications
  • Domain Expertise: Solid understanding of well operations, drilling logistics, production data, and scheduling workflows.
  • Experience working with large-scale or streaming datasets.
  • Experience with mathematical modeling and optimization libraries (SciPy, PuLP, OR-Tools).
  • Experience setting up CI/CD pipelines and container deployments on GCP.

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