Quantitative Developer - New York

PRI Global

$100K — $150K *
Finance & Insurance
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of Python development experience
  • Strong analytical thinking and problem-solving skills
  • Background in finance or risk management
  • Proficient in quantitative modeling and scenario analysis
  • Experience with data engineering and large datasets
  • Familiarity with REST APIs and front-end technology
  • Knowledge of libraries such as Pandas and Numpy

Responsibilities

  • Develop and implement balance sheet projections using Python
  • Support regulatory and ad hoc scenario analyses for Treasury and risk
  • Build tools for sensitivity calculations and stress analytics
  • Design high-performance Python modules for scenario analysis
  • Integrate financial datasets using SQL for comprehensive analyses
  • Collaborate with UI developers on React-based dashboards
  • Enhance workflow through API development and integration

Benefits

  • Hybrid work environment with flexibility
  • Opportunity to work on long-term impactful projects
  • Collaboration with cross-functional teams
  • Exposure to high-level decision-makers in finance
  • Access to advanced tools and technology in quantitative analysis
Full Job Description
Job Title: Quantitative Developer

Location: New York (240 Greenwich St, New York, NY 10286) - Hybrid Role

Long Term Project

Job Description: We are seeking a Sr Python Developers with strong Python skills, analytical thinking, and financial/risk experience to help with system design and implement the core modeling, scenario generation, and analytics components of this enterprise platform.

This role blends quantitative development and software engineering to build scalable tools used by Treasury, Market Risk, and senior decision-makers.

Key Responsibilities

Quantitative Modeling & Scenario Analytics
• Develop and implement using Python for balance sheet projections, interest rate risk (IRR), liquidity analytics, and scenario-driven stress testing.
• Support both regulatory scenarios (e.g., CCAR, SCB, liquidity stress) and ad hoc "what-if" analyses for Treasury and risk stakeholders.
• Build tools for scenario transformations, sensitivity calculations, curve construction, and quantitative stress analytics.

Platform & Data Engineering
• Design and maintain high performance Python modules that serve as the computational core of the scenario analysis framework.
• Proficient with Pandas, Numpy and other Quant libraries.
• Work with large datasets using SQL to integrate financial, balance sheet, and market inputs.
• Collaborate on the development of REST APIs that interface with scenario engines, model layers, and user applications.

Front-End & Workflow Integration
• Partner with UI developers to support React-based dashboards that present scenario results, visualizations, and analytics to business users.

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