Senior Quant Trader - TIER 1 QUANT FIRM
Pagos Consultants, New York, NY, United States
Quantitative Trader/Portfolio Manager | Tier 1 Quant Trading Firm | $300K+ Base + Performance-Based Compensation, no earnings ceiling.
We are partnering with a
tier-1 quantitative trading firm
renowned for its scientific rigour, technological innovation, and industry-leading infrastructure. With over $20 billion USD in assets under management and a presence across major financial hubs, the firm is expanding its elite team of quantitative researchers, traders, and engineers to drive the next phase of growth in algorithmic trading experience.
Experience They seek exceptional individuals with deep expertise in systematic trading strategies, open to all asset classes (equities, fixed income, commodities, FX, derivatives, crypto, etc.) and flexible across trading horizons (high-frequency, mid-frequency, or long-term statistical arbitrage).
Ideal Candidate Profile
Institutional quant background: Proven track record within an institutional quantitative trading environment
Exceptional analytical foundations: Advanced degree (PhD/MS) in Mathematics, Computer Science and Physics
Strategic versatility: Expertise in alpha research, signal generation, or portfolio optimisation, with the ability to adapt strategies across asset classes and regimes.
Contact
Connor Akers
or
Dan Raza
directly to be considered.
#J-18808-Ljbffr
We are partnering with a
tier-1 quantitative trading firm
renowned for its scientific rigour, technological innovation, and industry-leading infrastructure. With over $20 billion USD in assets under management and a presence across major financial hubs, the firm is expanding its elite team of quantitative researchers, traders, and engineers to drive the next phase of growth in algorithmic trading experience.
Experience They seek exceptional individuals with deep expertise in systematic trading strategies, open to all asset classes (equities, fixed income, commodities, FX, derivatives, crypto, etc.) and flexible across trading horizons (high-frequency, mid-frequency, or long-term statistical arbitrage).
Ideal Candidate Profile
Institutional quant background: Proven track record within an institutional quantitative trading environment
Exceptional analytical foundations: Advanced degree (PhD/MS) in Mathematics, Computer Science and Physics
Strategic versatility: Expertise in alpha research, signal generation, or portfolio optimisation, with the ability to adapt strategies across asset classes and regimes.
Contact
Connor Akers
or
Dan Raza
directly to be considered.
#J-18808-Ljbffr