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ALGOQUANT

Quantitative Trader

United Kingdom
Posted about 22 hours ago
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Quantitative Traders & Trading Pods

AlgoQuant Asset Management
UAE · EU · UK – Reports to Head of Trading – Rolling start – Individual, seeded-capital, and pod lift-out tracks

About AlgoQuant

AlgoQuant Asset Management is a multi-strategy digital asset manager allocating capital across 25+ internal and external quantitative trading pods. Founded in 2018, we’ve grown into an institutional platform that pairs real trading edge with strong governance and advanced technology, serving family offices and institutional investors globally.

We are scaling deliberately: adding standout individual traders, backing established pods with capital and infrastructure, and building out strategies that bridge traditional finance and digital assets, including the fast-growing real-world asset (RWA) space. AI runs through how we operate, from research and signal generation to execution and monitoring.

Who we’re hiring

This is a single, open search across two tracks. We want the best market operators we can find, whether you trade solo or lead a team.

  • Individual traders who want real ownership of live risk, a direct line to research and engineering, and a genuine voice in how we trade.
  • Pods and teams with a coherent, attributable track record who want institutional capital, prime and venue access, execution infrastructure, and strong governance behind them, whether through a seeded-capital arrangement or a full lift-out.

The role

You’ll sit right at the intersection of live execution and quantitative research. You’ll manage live positions across spot, derivatives, structured products, and increasingly tokenized real-world assets, working closely with researchers and engineers to see our models perform in the real world, not just on paper.

This is a role for people who love the markets, think in data, and want real ownership over how capital moves, from model logic to risk limits to venue and counterparty relationships.

How we work

Traders lead development here. You own the trading direction and the requirements; our developers and engineers own the technical build. The logic is simple: you stay focused on the markets and the trade, while they turn your requirements into fast, reliable infrastructure. We expect you to know exactly what you want and to communicate it clearly, not to spend your day writing production code.

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.

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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.

P

Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your 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.

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It searches the market for you

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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.

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Strong

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.

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Strong

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.

AI is central to how we operate. We use machine learning and modern AI tooling across research, signal generation, execution, and monitoring, and we want traders who treat AI as a practical edge and push us to use it better.

What you’ll do

  • Execute and manage live positions across spot, perpetuals, options, and structured products on digital asset venues
  • Monitor open positions, Greeks, funding rates, and cross-venue exposure in real time, and act fast when it matters
  • Dig into execution quality, slippage, market impact, and fill rates, and turn what you find into real improvements to our models and infrastructure
  • Set the requirements for the models and execution tooling you need, and work closely with developers to build them, so your time stays on trading
  • Put AI and machine learning to work across signal generation, execution quality, and monitoring, and help shape how the desk adopts new tooling
  • Partner with quant researchers to turn signals and strategy logic into sharp, capital-efficient trading plans
  • Build strong relationships with exchanges, prime brokers, OTC desks, and counterparties
  • Help bring new strategies and venues online: test execution, validate connectivity, and give the green light for live trading
  • Contribute to our execution infrastructure, tooling, and real-time monitoring dashboards

Strategy areas we’re investing in

  • Digital assets (core): Spot and derivatives across major centralized venues, on-chain markets and DeFi execution, market-neutral and directional systematic strategies.
  • TradFi and RWA crossover (named specialism): We are actively expanding into strategies that carry proven traditional-finance approaches into digital and tokenized markets. Relevant backgrounds include fixed income and rates, credit, commodities, FX, and equity or futures relative value, applied to areas such as tokenized treasuries and money-market instruments, on-chain credit and private credit, basis, carry, and cash-and-carry arbitrage, and yield and funding strategies that span CeFi, DeFi, and RWA venues. If you have run TradFi strategies and want to apply that edge in digital and tokenized markets, we want to talk.

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What we’re looking for

  • Direct experience trading in a live, capital-at-risk environment: prop trading, market making, hedge fund execution, or a systematic trading desk
  • Strong knowledge of your market. For digital assets, that means spot and derivatives venues (Binance, OKX, Deribit, Bybit, Hyperliquid), market microstructure, and funding dynamics. For TradFi and RWA candidates, deep fluency in your asset class and its microstructure, and a clear view on how it translates to tokenized markets
  • Comfort with options and derivatives, including Greeks, vol surface dynamics, and hedging in fast-moving markets
  • A quantitative mindset, comfortable using Python for execution analysis, strategy monitoring, and tooling, with experience in order management systems and execution APIs
  • A clear sense of what you want from your models and tools, and the ability to brief and direct developers to get it built: you lead, they engineer
  • Comfort using AI and machine learning as practical tools across research, execution, and workflow, including modern LLM and agentic tooling
  • The ability to work within, and improve on, existing execution and risk infrastructure while helping drive toward new markets and opportunities
  • Clear, confident communication, especially when things move fast
  • Experience with on-chain markets and DeFi execution (Hyperliquid, GMX, perpetual DEXes) is a strong plus
  • For senior candidates and pod leads, a live, attributable track record including P&L ownership and measurable execution alpha

For pods and teams

If you’re bringing a team, we’ll also want to understand a few specifics so we can move quickly:

  • Team size, roles, and how long you’ve traded together
  • Strategy capacity, target markets, and the infrastructure you run on today
  • An attributable, risk-adjusted track record (Sharpe, drawdown, capacity, and turnover)
  • What you’re looking for from a platform: capital, leverage, venue and prime access, technology, or all of the above
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Skills

Quantitative Trading
Market Microstructure
Risk Management
Execution Analysis
Python
Machine Learning
AI
Derivatives
Digital Assets
Trading Strategies
Communication
Team Leadership
Execution Infrastructure
Real-Time Monitoring
Capital Management
Relationship Building

Location

United Kingdom

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