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Quantitative Analyst - Crypto & FX

Early Applicant
  • Posted 18 hours ago
  • Be among the first 10 applicants

Job Description

The Quantitative Researcher plays a critical role in developing proprietary quantitative trading strategies that drive the firm's trading performance across Crypto, Forex, and Global Equity markets. This role is ideal for someone passionate about mathematics, statistics, machine learning, and financial markets, with the ability to transform complex market data into scalable and profitable trading strategies. You will work closely with the CEO and engineering teams to research, validate, and deploy systematic trading models into live trading environments.

What You'll Be Doing:

  • Research and develop proprietary quantitative trading strategies across Crypto, Forex, and Equity markets.
  • Analyze large-scale historical and real-time market data to identify alpha opportunities and market inefficiencies.
  • Design and implement statistical models and quantitative signals using Python.
  • Build, backtest, simulate, and validate systematic trading strategies before production deployment.
  • Evaluate model performance, robustness, risk, and execution efficiency.
  • Collaborate with engineers to optimize strategy implementation and production systems.
  • Continuously improve existing strategies through data-driven research and experimentation.
  • Stay up to date with academic research and emerging quantitative trading techniques.

What We're Looking For:

  • Master's degree in Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or another quantitative discipline.
  • 1–3 years of experience in quantitative research, systematic trading, or financial modeling.
  • Strong foundation in probability, statistics, optimization, stochastic processes, and numerical methods.
  • Advanced proficiency in Python, including Pandas, NumPy, and SciPy.
  • Experience building quantitative models, backtesting frameworks, and statistical analysis tools.
  • Solid understanding of market microstructure and electronic trading systems.
  • Working knowledge of C++ is an advantage.
  • Strong analytical thinking, problem-solving, and research capabilities.
  • Ability to work independently while managing multiple research initiatives in a fast-paced environment.

Preferred Experience:

  • Experience working in proprietary trading firms, hedge funds, market-making firms, or quantitative investment teams.
  • Experience researching Crypto, FX, or Global Equity markets.
  • Knowledge of machine learning applications in quantitative finance.
  • Experience with Level 2 and Level 3 market data.
  • Familiarity with high-frequency trading concepts and execution algorithms.
  • Experience deploying research models into production trading environments.
  • Strong understanding of risk-adjusted portfolio construction and performance evaluation.

Interview Process:

Stage 1 – Initial Interview (HR Screening)

Introduction, career background, communication skills, and role alignment.

Stage 2 – Technical Interview

Discussion on quantitative research experience, statistical modeling, programming, and trading knowledge.

Stage 3 – Quantitative Research Assessment

Candidates will complete a technical assessment covering quantitative reasoning, statistical concepts, research methodology, and critical thinking, followed by a discussion of their approach and findings.

About IUX

At IUX, we are more than just a brokerage firm – we are a global fintech with a presence spanning Asia, MENA, and Latin America. As we continue to expand into Europe and beyond, we are seeking top talent to join our dynamic team. Our mission To revolutionize the trading experience through cutting-edge technology, seamless execution, and a client-centric approach. If you're looking for a fast-paced environment where innovation meets opportunity, IUX is the place for you!

All applications will be treated in strict confidence. By submitting your application, you consent to our privacy policy regarding the collection and use of your personal data. Only shortlisted candidates will be notified.

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About Company

Job ID: 152201783

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