Clearwater Analytics is the leading SaaS platform for investment accounting risk and performance serving the world’s largest insurance companies asset managers and institutional investors. As a Risk Quantitative Developer you will play a critical role within the Quant team helping to enhance and expand our Multi-Asset-Class risk analytics capabilities including instrument valuation and risk estimation methods. You will work closely with cross-functional teams of developers and interact directly with clients to deliver solutions that focus on both developers and end-users with a primary emphasis on risk management.

Quantitative Development

• Design implement and maintain pricing libraries and risk models covering Fixed Income Credit and Derivatives instruments.
• Build platform capabilities for scenario analysis risk sensitivities (DV01 CS01 Greeks) P&L attribution and cash flow generation.
• Identify and advocate for new models and design patterns to support an evolving instrument universe and client base.

Technical Development

• Design and build robust maintainable software systems with a focus on performance correctness and extensibility.
• Write clean well-tested code and contribute to code reviews technical documentation and shared libraries.
• Proactively identify and resolve technical debt performance bottlenecks and gaps in test coverage.

Collaboration & Mentorship

• Mentor engineers at all levels and contribute to a culture of continuous learning.
• Engage directly with clients to deliver customized risk solutions and platform integrations.
• Communicate complex quantitative topics clearly to technical and non-technical stakeholders alike.

Experience & Skills

• 9+ years of quantitative development in financial services preferably in a front-office or risk technology environment.
• Expertise in risk and valuation analytics across Fixed Income Credit and/or Derivatives asset classes.
• Strong Python proficiency; experience with C++ or Java is a plus.
• Solid grounding in quantitative finance: yield curve construction credit spread modeling and standard risk sensitivities.
• Experience with distributed systems and microservices on public cloud (AWS Azure or GCP).
• Proven ability to lead technical delivery across multi-team projects as a tech lead or senior contributor.

Education

• Bachelor’s or Master’s degree in Mathematics Physics Financial Engineering Computer Science or a related quantitative field.