Senior Quant Risk Developer — Multi-Asset Pricing

Clearwater Analytics (CWAN)

New York

Hybrid

USD 179,000 - 243,000

Full time

14 days+
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Benefits offered by this job

Health insurance
401(k)
Paid time off
Parental leave
Medical leave
Disability insurance

Job summary

Clearwater Analytics is seeking a Risk Quantitative Developer to join the Quant team in New York. You will design, implement, and maintain pricing libraries and risk models for Fixed Income, Credit, and Derivatives, while building analytics for scenario analysis and risk sensitivities.

You will mentor engineers, collaborate with clients, and contribute to robust, well-tested software across distributed systems.

Qualifications

  • 9+ years of quantitative development in financial services.
  • Expertise in risk and valuation analytics across Fixed Income, Credit, and/or Derivatives.
  • Strong Python; C++ or Java is a plus.
  • Experience with distributed systems and cloud deployments (AWS/Azure/GCP).
  • Lead technical delivery across multi-team projects.

Responsibilities

  • Design, implement, and maintain pricing libraries and risk models for Fixed Income, Credit, and Derivatives.
  • Build capabilities for scenario analysis, DV01/CS01, P&L attribution, and cash flow generation.
  • Mentor engineers and interact with clients to deliver risk solutions.
  • Write clean, well-tested code and contribute to documentation and reviews.

Skills

Python
C++
Java
Distributed systems
Cloud computing
Quantitative finance
Yield curve
Credit spread
Risk sensitivities
Front-office experience

Education

Bachelor’s or Master’s in Mathematics/Physics/Financial Engineering/CS

Tools

Git
CI/CD
Unit testing

Job description

Clearwater Analytics is seeking a Risk Quantitative Developer to join the Quant team in New York. You will design, implement, and maintain pricing libraries and risk models for Fixed Income, Credit, and Derivatives, while building analytics for scenario analysis and risk sensitivities.

You will mentor engineers, collaborate with clients, and contribute to robust, well-tested software across distributed systems.

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