Senior Quantitative Developer
Scalp Trade LLC
Job Description
Job Description
Position Overview
We are seeking an experienced developer with a strong understanding of options theory and derivatives pricing who can translate quantitative research into production trading systems. The ideal candidate understands both the underlying theory and the engineering required to build reliable, low-latency software. Working closely with traders and quantitative researchers, the candidate will transform theoretical pricing models into practical, production-ready implementations, making sound engineering decisions where theory and real-world constraints diverge. This role provides significant ownership over the architecture, design, and implementation of the firm's core pricing technology.
Key ResponsibilitiesDesign and implement real-time theoretical pricing models for options
Design and implement numerical methods that balance theoretical accuracy with production performance
Improve pricing accuracy, computational efficiency, and performance under high-throughput market conditions
Work with traders and quantitative researchers to implement and refine theoretical pricing models
Participate in architecture design decisions related to scalability, latency, resiliency, and data integrity
Collaborate with engineering and trading teams to define technical requirements and deliver production-quality software
Strong understanding of options pricing theory and derivatives markets
Experience implementing quantitative pricing models in production software
Strong background in numerical methods, optimization, and computational mathematics
Extensive experience developing production trading systems in C++
Experience working with APIs, multithreaded systems, and low-latency applications
Strong analytical and problem-solving skills with the ability to understand complex software systems and quantitative models
Ability to work independently in a fast-moving development environment
Ability to balance quantitative rigor with practical engineering constraints when implementing production trading systems
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