Crypto Quant Researcher (Strategy Builder)ID:59315

13,000 MYR ~ 16,000 MYRBukit Bintang/KLCCabout 4 hours ago

Overview

  • Salary

    13,000 MYR ~ 16,000 MYR

  • Industry

    Web/Mobile/Game, Software/Information Processing, IT/Telecommunications, Trading Firm, Other

  • Job Description

    About Us
    We are building a next gen quantitative trading and research platform focused on systematic, data driven alpha generation across crypto markets. This is not a signal copying or indicator tuning role we want people who design, test, break, and rebuild their own strategies from first principles

    Role Overview
    You will research, design, backtest, and iterate original crypto trading strategies across spot, perpetuals, and derivatives. You will work closely with engineering and trading to convert ideas into production ready systems.

    Key Responsibilities
    - Design original crypto trading strategies (momentum, mean reversion, market structure, volatility, funding, microstructure, etc.)
    - Build and maintain backtesting pipelines using historical crypto data (tick, OHLCV, funding, order book if available)
    - Perform rigorous statistical evaluation (drawdowns, regime behavior, robustness, overfitting checks)
    - Iterate strategies based on failure analy sis, not curve fitting
    - Research and engineer custom features/factors beyond standard indicators
    - Document strategy logic, assumptions, and failure modes clearly
    - Collaborate with engineers to move research into live trading systems

Qualifications

  • Requirement

    MUST
    - Hands on experience developing crypto trading strategies
    - Strong quantitative foundation (math, stats, probability)
    - Proficiency in Python (NumPy, Pandas, vectorized)
    - Experience working with crypto market data (spot/funding rates)
    - Deep understanding of market microstructure and crypto specific mechanics
    - Ability to explain why a strategy should work, not just that it backtests well

    Strongly Preferred
    - Live or paper traded strategies with real performance data
    - Experience with derivatives, funding rate dynamics, liquidations
    - Familiarity with event driven or low latency backtesting frameworks
    - Experience handling noisy, imperfect data
    - Knowledge of regime detection, volatility clustering, or nonlinear effects
    - Prior work at a prop shop, hedge fund, or serious personal trading operation

    Added Advantaged
    - GitHub with backtesting or trading projects
    - Trading journals or research notes
    - Prior PnL (even small size honesty matters more than scale)

  • English Level

    -

  • Other Language

    English

Additional Information

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