Quant Trader – Crypto Markets & Automated Strategies

Caladan

Singapore

On-site

SGD 120,000 - 180,000

Full time

2 days ago
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Job summary

Caladan is seeking a Quant Trader to design, implement and manage systematic trading strategies across digital asset markets. You will work closely with trading, research, and technology teams to identify alpha opportunities, refine pricing and execution models, and manage risk across the firm's portfolio.

The ideal candidate has an academic background in Mathematics, Computer Science, Engineering, or a related field, with experience in high-frequency or proprietary trading, especially in crypto

Qualifications

  • Background in Mathematics, Computer Science, Engineering, or related field.
  • Experience in high-frequency or proprietary trading, especially in crypto or digital asset markets.
  • Experience designing or supporting automated trading strategies with multi-leg or cross-venue execution.
  • Process-oriented mindset with focus on building/refining research processes and capabilities.
  • Comfort operating in high-ambiguity environments and iterating quickly.

Responsibilities

  • Deploy and refine quantitative trading strategies across a multi-venue, multi-asset portfolio.
  • Monitor live strategy performance and adjust parameters as conditions change.
  • Collaborate with engineering teams to improve execution infrastructure, latency, and connectivity across venues.
  • Conduct research into market microstructure, liquidity dynamics, and pricing inefficiencies.
  • Manage position and risk limits in line with firm-wide risk policy.

Skills

Quantitative trading
High-frequency trading
Automated trading systems
Crypto markets
Multi-venue execution

Education

Mathematics
Computer Science
Engineering

Job description

Caladan is seeking a Quant Trader to design, implement and manage systematic trading strategies across digital asset markets. You will work closely with trading, research, and technology teams to identify alpha opportunities, refine pricing and execution models, and manage risk across the firm's portfolio.

The ideal candidate has an academic background in Mathematics, Computer Science, Engineering, or a related field, with experience in high-frequency or proprietary trading, especially in crypto

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