Crypto Options QD

Option Quantitative Developer (Senior / Expert)

Overview

I am looking for an experienced option-focused quantitative developer to build and optimize our pricing, volatility, and risk-analysis infrastructure. The role requires strong numerical skills, deep understanding of option theory, and hands-on experience delivering production systems in fast-paced trading environments.

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Responsibilities
* Develop numerical engines for option pricing, stochastic-process simulation, volatility-surface modeling, and Greeks/hedging calculations.
* Build and optimize a low-latency C++ pricing and risk platform; improve algorithm efficiency, memory usage, and system stability.
* Convert quant research models into production workflows, including calibration, backtesting, validation, and deployment.
* Maintain data pipelines for historical and real-time data; ensure data accuracy and efficient schema design.
* Enhance backtesting tools, monitoring systems, and automated reporting modules.
* Contribute to architectural decisions and performance improvements across core components.

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Requirements

Background
* Master's degree or above in CS, EE, Financial Engineering, Applied Mathematics, or similar fields.
* 5+ years of derivatives/option quantitative development; experience in hedge funds, trading desks, or financial-engineering teams.
* 2+ years of crypto-options or crypto-quant development experience is strongly preferred.
* Previous involvement in market-making, real-time trading systems, or ultra-low-latency platforms.

Financial Engineering Skills
* Proficient in numerical methods for stochastic processes and computational finance.
* Strong command of option-pricing theory: Black-Scholes, volatility models such as SSVI/SABR, and full Greeks/hedging logic.
* Understanding of crypto-option microstructure, quoting behavior, and hedging workflows.
* Familiar with probability, time-series analysis, model validation, and backtesting methodology.

Technical Skills
* Excellent C++ skills: performance tuning, concurrency, memory management, and low-latency programming.
* Solid Linux experience; capable in network programming, multi-thread/multi-process design, async IO, and common middleware usage.
* Knowledge of time-series or columnar databases (ClickHouse, kdb+, TimescaleDB, Postgres, etc.).
* Able to use Python for modeling, prototyping, and research integration.
* Strong engineering discipline: testing, CI/CD, code review, and performance benchmarking.