Onyx Alpha Partners
Quant Trader - Systematic Options (Crypto)

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Quant Trader - Systematic Options (Crypto)
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?
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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


Get help with your application
Your very own career expert that helps elevate your application to the next level.
- 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.
- Compensation: £150k – £215k Base + Performance-Based Bonus
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.
Apply Now
At Onyx Alpha Partners, we are committed to connecting the most sought after talent in the financial world, to opportunities that expand the universe of unconstrained performance within their chosen discipline. If this opportunity aligns with your career aspirations, we encourage you to apply and explore the potential for growth and unparalleled success.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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