Quant/ Algorithm Developer

Quant/ Algorithm Developer (5)

Location: Pittsburg, PA / lake Mary, FL Hybrid Role

Long Term Project

Fl

Job Description:

The Treasury group of a large global bank is building a next generation scenario analysis and balance sheet modeling platform to support both regulatory and internal risk management needs.

We are seeking a Quant / Algorithm Developer with strong Python skills, analytical thinking, and financial/risk modeling experience to help 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.

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Key Responsibilities:

Quantitative Modeling & Scenario Analytics

Develop and implement Python-based quantitative models for balance sheet projections, interest Market 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.

Validate and enhance modeling logic based on financial theory and empirical data analysis.

Platform & Data Engineering

Design and maintain high performance Python modules that serve as the computational core of the scenario analysis framework.

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.

Contribute to workflow automation that improves consistency, transparency, and turnaround time for scenario production.

Collaboration & Governance

Work with Treasury, Market Risk, and Finance teams to translate business and regulatory requirements into quantitative specifications.

Ensure models and analytics meet governance expectations, including documentation, version control, and testing standards.

Participate in model enhancements, performance tuning, and scalability design across the analytics pipeline.

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Required Skills

Quantitative & Technical Skills

Strong proficiency in Python for numerical programming, data analysis, and model development.

Proficiency in SQL for data extraction, transformation, and performance tuned queries.

Experience building or integrating REST APIs for model-to-application communication.

Familiarity with scientific libraries such as NumPy, Pandas, SciPy, and exposure to distributed compute frameworks.

• Financial & Risk Domain Knowledge
  • Understanding of financial instruments, banking products, or portfolio dynamics.
  • Experience with one or more of the following:
• Interest Market Risk (IRR/NII/EVE)
• Liquidity risk and cashflow modeling
• Market Risk or sensitivity-based analytics
• Capital stress testing (e.g., CCAR)
  • Ability to work with financial data, time-series analysis, and scenario-based modeling techniques.
• Soft Skills
  • Strong analytical thinking and problem solving ability.
  • Clear communication skills, especially for explaining technical concepts to non technical partners.
  • Ability to collaborate with risk SMEs, quants, and technology teams.
  • Self starter comfortable working in a fast-paced, multi-stakeholder environment.

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Preferred Qualifications

• • Master's degree in Quantitative Finance, Mathematics, Engineering, Computer Science, or similar field.
  • Experience in Treasury, risk modeling, or regulatory stress testing within financial services.
  • Exposure to React or willingness to collaborate closely with front-end developers.
  • Experience with cloud technologies, Git, CI/CD, or workflow orchestration tools.