Staff Quantitative Developer

Clearwater Analytics•New York, NY

About The Position

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.

Requirements

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

Responsibilities

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.
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.
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.