At a Glance
- Tasks: Develop mathematical models and design algorithmic trading strategies in digital asset markets.
- Company: Join a global digital-asset proprietary trading firm with a forward-thinking culture.
- Benefits: Remote work, flexible hours, 38 days paid vacation, and a supportive team environment.
- Why this job: Make an impact in the fast-paced world of digital assets and quantitative trading.
- Qualifications: Strong programming skills in Python and experience in algorithmic trading or data science.
- Other info: Exciting opportunities for career growth and autonomy in a dynamic environment.
The predicted salary is between 36000 - 60000 ÂŁ per year.
Join to apply for the Quant Trader / Researcher role at ICEO - Venture Builder. We are looking for a Quant Trader / Quantitative Researcher to support our trading team by developing mathematical models, analyzing large datasets, and designing algorithmic trading strategies across digital asset spot and derivatives markets. You will work closely with traders, engineers, and product teams to identify inefficiencies, optimize execution, and contribute to the build‑out of systematic strategies and risk models. You would be joining a global digital‑asset proprietary trading firm operating across major centralized exchanges. Our team runs multiple strategies, including market making, arbitrage, and systematic trading where both technology and quantitative research play a central role in our performance.
Key Responsibilities
- Strategy Research & Development: Research, design, and prototype systematic trading strategies across spot, perp, and funding markets. Identify alpha opportunities using statistical, ML‑based, or microstructure‑driven approaches. Analyze exchange data (order books, trades, liquidations, funding rates, volatility) to detect patterns and market regimes. Develop predictive models for price movements, volatility surfaces, order flow imbalance, and liquidity conditions.
- Backtesting & Simulation: Build robust backtesting frameworks that accurately model exchange mechanics (fees, funding, latency, depth, liquidation rules, etc.). Run simulations to evaluate performance, edge stability, and risk exposure under different market regimes. Validate strategy assumptions with sensitivity and stress tests.
- Production Deployment: Implement models into production trading systems in collaboration with engineering. Monitor live strategy performance and adjust parameters according to market dynamics. Contribute to execution systems, including smart routing, hedging logic, and risk overrides.
- Risk Management: Build and maintain models for PnL attribution, risk exposure, slippage, and tail events. Develop monitoring tools for leverage, liquidity crunches, and liquidation cascades. Provide insight into market microstructure risks across CeFi and DeFi venues.
- Research & Market Intelligence: Track exchange‑level changes (funding mechanisms, fee structures, margin rules). Analyze competitor markets, price indexes, and cross‑exchange spreads. Support internal teams (Product, Lending, Derivatives, Strategy) with quantitative insights.
Qualifications
- Technical Skills: Strong programming skills in Python, C++, or Rust (Python required). Familiarity with distributed computing, large dataset handling, and time‑series databases. Knowledge of probability, statistics, optimization, and numerical methods. Experience with algorithmic trading, HFT, or market‑making strategies.
- Domain Experience: Experience with digital assets, perpetual futures, funding rates, liquidations, index/mark prices, or CEX/DEX microstructure is highly preferred. Understanding of leverage/margin systems and risk models is a plus. Prior work on cross‑exchange arbitrage, statistical arbitrage, execution algorithms, or options/vol surfaces is beneficial.
- Soft Skills: Highly analytical and comfortable with ambiguity. Ability to translate mathematical ideas into production‑level code. Strong communication skills for working with traders, engineers, and product teams. Self‑driven, curious, and excited to solve complex quantitative problems.
Advantage if you have
- Experience with reinforcement learning or deep learning applied to trading.
- Contributions to open‑source quant/trading libraries.
- Background in cryptography, distributed systems, or blockchain networks.
- Experience with real‑time systems or low‑latency infrastructure.
- Degree in Math, Physics, CS, Engineering, Statistics, or related discipline.
- At least 5 years of experience in a quant, algo trading, or data science role.
What we offer
- Remote‑first company – you can work from anywhere in the world.
- Flexible working hours – we have core working hours (11 am–3 pm CET) with flexibility outside those hours.
- 38 days of paid vacation leave per year + 14 days of paid sick leave.
- Forward‑thinking team with autonomy to make choices and explore new ideas.
The recruitment process
- Stage 1: Screening with TA Partner – basic information about ICEO, the project, the role, and the offer. General questions about your experience (about 30 min).
- Stage 2: Interview with Senior Trading Analyst – focus on domain check: trading strategies, order execution, modeling, analysis, etc. (30 min).
- Stage 3: Interview with Head of Technology – focus on tech and infra understanding: coding skills, order routing, algos, etc. (30 min).
- Stage 4: Final interview with CEO of the venture – focus on overall company and culture fit (30 min).
Seniority level: Not Applicable
Employment type: Full‑time
Job function: Finance and Sales
Industries: Internet Publishing
Quant Trader / Researcher in Warwick employer: ICEO - Venture Builder
Contact Detail:
ICEO - Venture Builder Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quant Trader / Researcher in Warwick
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even online forums related to quant trading. The more people you know, the better your chances of landing that dream role.
✨Show Off Your Skills
Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your projects, models, or any algorithmic strategies you've developed. This will give potential employers a taste of what you can bring to the table.
✨Ace the Interview
Prepare for those interviews by brushing up on both technical skills and soft skills. Practice coding challenges and be ready to discuss your thought process. Remember, they want to see how you think as much as what you know!
✨Apply Through Our Website
Make sure to apply directly through our website! It not only shows your interest but also gives you a better chance of being noticed. Plus, we love seeing candidates who take that extra step!
We think you need these skills to ace Quant Trader / Researcher in Warwick
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Quant Trader / Researcher role. Highlight relevant experience, especially in algorithmic trading and quantitative research. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter should tell us why you're excited about this role and how you can contribute to our team. Share specific examples of your past work that relate to the responsibilities listed in the job description.
Showcase Your Technical Skills: Since we're looking for strong programming skills, make sure to mention your proficiency in Python, C++, or Rust. If you've worked with large datasets or developed predictive models, let us know!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates during the process!
How to prepare for a job interview at ICEO - Venture Builder
✨Know Your Models Inside Out
Make sure you can explain your mathematical models and trading strategies clearly. Be prepared to discuss how you developed them, the data you used, and the results you achieved. This will show your depth of understanding and ability to communicate complex ideas.
✨Brush Up on Technical Skills
Since strong programming skills in Python are a must, practice coding problems related to algorithmic trading. Familiarise yourself with backtesting frameworks and be ready to demonstrate your coding abilities during the technical interview stage.
✨Stay Updated on Market Trends
Research current trends in digital assets and algorithmic trading. Being able to discuss recent market changes or competitor strategies will impress the interviewers and show that you’re proactive about staying informed.
✨Prepare for Team Collaboration Questions
Expect questions about how you work with traders, engineers, and product teams. Think of examples where you successfully collaborated on projects, highlighting your communication skills and ability to translate complex concepts into actionable insights.