Quant/ Algorithm Developer

Lakshya TechContract
Pennsylvania
7 - 10 YearsMar 4th, 2026
95 ViewsBe an Early Applicant
Required Skillset:
PythonMarket RiskInterest Rate RiskSQLREST APILiquidity riskCapital stress testingTime-series analysisScenario-based modelling

Job Description

  • The Treasury group of a large global bank is building a next generation scenario analysis and balance sheet modelling 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 modelling experience to help design and implement the core modelling, 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.

 

•        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.

 

Experience with one or more of the following:

  • Interest Rate Risk (IRR/NII/EVE)
  • Liquidity risk and cashflow modelling
  • Market Risk or sensitivity-based analytics
  • Capital stress testing (e.g., CCAR)

•  Ability to work with financial data, time-series analysis, and scenario-based modelling 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.

 

Preferred Qualifications

•        Master’s degree in quantitative finance, Mathematics, Engineering, Computer Science, or similar field.

•        Experience in Treasury, risk modelling, or regulatory stress testing within financ

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