Full-Stack Python Engineer

ZipStaff Inc.; McLean (VA); On-site; USD 120,000 - 150,000; Full time

Benefits offered by this job

Health Insurance

Dental Insurance

Vision Insurance

401(k) + 401(k) matching

Paid time off

Referral Program

Job summary

ZipStaff Inc. is seeking a Full-Stack Python Engineer for financial modeling, analytics, and research systems at a leading housing-finance organization in McLean, VA. This is a hands-on, on-site role focusing on Python and web tech, not a data-science or front-end-only position.

You will design, develop, and support analytics systems for market and credit risk, review code, and collaborate with finance researchers to define requirements.

Qualifications

• 5+ years developing analytics software, or a Master’s with 2+ years.
• Bachelor’s or Master’s in CS, SE, or a related field.
• Python with Flask, Dash and data processing with Pandas/NumPy.
• Web apps: HTML, CSS, JavaScript; production code; React is a must-have.
• SQL and relational databases.
• Linux/Unix operating environment.
• Demonstrated knowledge of quantitative finance.
• Ability to work on-site in McLean, VA.
• Must be legally authorized to work in the United States without sponsorship.

Responsibilities

• Design, develop, and support systems in financial modeling, analytics, and research.
• Write new code and review changes against standard engineering practices.
• Support operational execution of software used to monitor and control market and credit risk.
• Modify and maintain analytics applications.
• Help financial research and engineering define application requirements.

Skills

Python

Flask

Dash

Pandas

NumPy

HTML/CSS/JS

SQL

Linux

Quant finance

React

Education

Bachelor's degree in CS/SE

Master's degree in CS/SE

Tools

React

Flask

Dash

Job description

Job Title: Full-Stack Python Engineer - Financial Analytics

Location: McLean, VA (On-site)

Employment Type: Contract (W2 through ZipStaff - No C2C or 1099)

About the Opportunity

ZipStaff is seeking a Full-Stack Python Engineer for financial modeling, analytics, and research systems at a leading housing-finance organization.

You will build and support applications used to monitor market and credit risk. This is a hands-on Python and web seat - not a data-science research role and not a front-end-only role.

What You'll Do:

• Design, develop, and support systems in financial modeling, analytics, and research.
• Write new code and review changes against standard engineering practices.
• Support operational execution of software used to monitor and control market and credit risk.
• Modify and maintain analytics applications.
• Help financial research and engineering define application requirements.

Required Qualifications:

• 5+ years developing analytics software applications, or a Master's in Computer Science, Software Engineering, or a related field with 2+ years.
• Bachelor's or Master's in Computer Science, Software Engineering, or a related technical field.
• Practical Python, including web technologies (Flask, Dash) and data processing (Pandas, NumPy).
• Web applications: HTML, CSS, JavaScript, and the ability to write production code (React is in the must-have line).
• SQL and relational databases.
• Linux / Unix.
• Demonstrated knowledge of quantitative finance.
• Ability to work on-site in McLean, VA.
• Must be legally authorized to work in the United States without sponsorship now or in the future.

Preferred Qualifications:

• AI experience, including LLMs used to build agentic applications.
• JavaScript frameworks (jQuery, DataTables, React) and front-end design (CSS, Tailwind).
• Cloud: Google Kubeflow or AWS.
• Fixed income, accounting, or capital markets.
• Mortgage or housing-finance (GSE) experience.
• R, Java, C, C++, or SAS.

Benefits:

• Health Insurance.
• Dental Insurance.
• Vision Insurance.
• 401(k) + 401(k) matching.
• Paid time off.
• Referral Program.

About ZipStaff:

ZipStaff partners with leading organizations to connect skilled technology professionals with high-impact contract opportunities. We focus on quality matches, clear communication, and long-term success for candidates and clients.