Remote Digital-Asset Quant Trader: Market Structure

Anemoi Predictive Technology LLC

Atlanta, Northern (GA, KY)

Hybrid

USD 185,000 - 280,000

Full time

14 days+
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Benefits offered by this job

401(k) plan with company matching
Remote-work equipment and home-office
Flexible paid time off
Paid parental and caregiver leave
Learning budget
Equity eligibility

Job summary

Anemoi Predictive Technology LLC is seeking a fully remote Digital-Asset Quantitative Trader based in the Atlanta, GA area to build a controlled institutional process for liquid digital-asset markets. The role coordinates pre-market readiness and full-session decisions in Eastern Time and involves ensuring evidence supports decisions for production readiness.

You will work with a small team to manage continuous-market exposure, venue risk, and weekend controls, emphasizing scalable processes,

Qualifications

  • Five+ years in quantitative trading, including digital assets.
  • Strong Python and statistics foundations for market analysis.
  • Experience with exchange APIs and venue risk management.

Responsibilities

  • Monitor continuous-market exposure, liquidity, and funding across venues.
  • Evaluate execution across centralized venues.
  • Design weekend and overnight operating controls.
  • Research market structure while respecting legal and counterparty limits.
  • Own continuous-market exposure and shift handoffs during Eastern Time coordination.

Skills

Quantitative trading
Python
Statistics
Operational discipline
Digital assets

Tools

Exchange APIs

Job description

Anemoi Predictive Technology LLC is seeking a fully remote Digital-Asset Quantitative Trader based in the Atlanta, GA area to build a controlled institutional process for liquid digital-asset markets. The role coordinates pre-market readiness and full-session decisions in Eastern Time and involves ensuring evidence supports decisions for production readiness.

You will work with a small team to manage continuous-market exposure, venue risk, and weekend controls, emphasizing scalable processes,

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