Quant Trader - Systematic Options (Crypto)

Onyx Alpha Partners; Greater London; On-site; GBP 180,000 - 320,000; Full time

Job summary

Onyx Alpha Partners in London seeks a Systematic Options Quant Trader to join a research-to-production seat at the intersection of volatility modelling, systematic quoting, and live risk management.

You will own live trading performance in crypto options across liquid venues, building robust surface models and a fast quoting engine while hedging with limited infrastructure.

Qualifications

• 5–7 years in systematic options trading, quantitative research, or electronic market making.
• Experience with live P&L or live quoting system ownership.
• Strong Python for research, backtesting, and surface simulation.
• Production experience in C++/Rust and low-latency systems.
• Familiarity with stochastic volatility frameworks (Heston, SABR, SVI).

Responsibilities

• Design and implement surface models robust to regime changes in crypto options.
• Build a latency-conscious quoting engine across fragmented 24/7 venues.
• Develop hedging frameworks for delta, gamma, and vega in thin liquidity markets.
• Take ownership of live trading performance and continuously improve models.

Skills

Python

C++

Rust

Live P&L

Quant research

Systematic options

Heston

SABR

SVI

Job description

Location: London

The Mandate

We are partnering with an established electronic market maker to place a Systematic Options Quant Trader in London. This is a research-to-production seat at the intersection of volatility modelling, systematic quoting, and live risk management.

The underlying is crypto options across highly liquid markets. This is not a directional crypto bet. It is a pure volatility and microstructure problem — the same class of problem you have been solving on equity index or FX underlyings, run on a market that is structurally less mature, analytically less crowded, and operationally open 24/7.

This is not a research-only role. You will be directly accountable for live trading performance.

The Hard Questions (What You Will Solve)

• Surface Construction Under Regime Instability: Crypto options markets exhibit vol surface dislocations that equity index vol does not — term structure inversions, smile collapses, and gap-risk-driven skew dynamics that don't resolve on a Heston calibration. How do you build a surface model that is both theoretically grounded and robust to a regime that is still being discovered?
• Execution-Aware Quoting in a Fragmented, 24/7 Venue Landscape: Unlike equity index options where the order book structure is well-defined, crypto options liquidity is fragmented across multiple venues, with asymmetric adverse selection profiles and queue dynamics that are not yet fully arbitraged. How do you bake that into a quoting engine that doesn't bleed edge to latency or flow toxicity?
• Greeks Hedging Without the Infrastructure Crutch: Automated delta, gamma, and vega hedging in a market with no designated market maker obligations, thinner futures liquidity at extremes, and periodic liquidity evaporation. How do you design a hedging framework that protects the book when the standard assumptions about hedge availability fail?

The Structural Edge

• The Problem Is Genuinely Unsolved: The vol modelling frameworks that dominate equity and FX options markets were calibrated over decades of institutional flow. In crypto options, you are working with a shorter history, structurally different participant composition, and surface dynamics that are still being mapped. If you want to be building the model rather than maintaining someone else's, this is that seat.
• Direct Research-to-Production Loop: The distance between Jupyter and live execution is short. You will see your model changes reflected in live quoting within days, not quarters. The feedback latency here is lower than at most established TradFi desks.
• Sophisticated Infrastructure, Without the Bureaucracy: You are plugging into a high-performance electronic market-making system. C++/Rust production environment, experienced engineering support, and a desk structure that does not require 14 layers of model approval.

Ideal Profile

• The Metric: 5–7 years in systematic options trading, quantitative research, or electronic market making. Your background is equity index, FX, or equity single-stock options — and you understand why the crypto vol surface is structurally different, not just superficially exotic. You have direct ownership of a live P&L or live quoting system, not just research contributions.
• The Tech: Python for research, backtesting, and surface simulation. C++, Rust, or equivalent for production. You have shipped models into live trading environments, not handed off to engineering. Comfort with stochastic vol frameworks (Heston, SABR, SVI) is expected — the ability to extend and break them is what this role demands.

Compensation & Preferences

• Non-compete: Preference for ≤12 months; buyouts considered for exceptional profiles.

This is not a guarantee of compensation or salary; a final offer amount may vary based on factors including but not limited to experience, domain expertise, and geographic location.