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Senior/Lead Quant (top tier fund)

New York, NY, US💼 Full-time🗓 2026-02-15 → 2026-07-29

Core

Generate original, high-conviction alpha signals across liquid global markets and turn them into production-ready alpha with measurable PnL impact.

Role type

Senior IC systematic alpha researcher

Builds

Production-ready alpha signals integrated into portfolio

Domain

Systematic trading / Quantitative finance

Deliverable

production ML models

Required skills

Statistical learning, time-series modeling, overfitting detection, cross-validation, experimental design, portfolio construction, signal interaction effects, Python, feature engineering, robustness analysis

Preferred skills

None stated

Technologies

Python

Responsibilities

Design rigorous research frameworks with out-of-sample validation and leakage control, stress-test ideas across regimes and liquidity conditions, work directly with decision-makers to allocate risk, improve research tooling and diagnostics

Seniority

Senior, hands-on IC

Rewrite
## Senior/Lead Quant (top tier fund) We’re looking for an exceptional, hands-on alpha researcher who can generate material PnL impact. This is not a support role. Not a junior seat. Not a “contribute to a signal library” position. This is for someone who can find real edges, validate them properly, and turn them into production-ready alpha. If you need bureaucracy, this won’t work. If you need intellectual challenge and real capital behind your ideas — read on. ### What You’re Here To Do - Generate original, high-conviction alpha signals across liquid global markets - Design rigorous research frameworks with proper out-of-sample validation and leakage control - Take signals from raw data → hypothesis → test → portfolio integration - Stress-test ideas across regimes, liquidity conditions, and structural breaks - Work directly with decision-makers to allocate risk to your research - Improve the research process itself — tooling, validation, feature engineering, diagnostics You are expected to materially move the needle. - Your research produces measurable PnL impact - You understand that most signals are noise — and act accordingly - You care more about robustness than backtest cosmetics - You know when to scale and when to kill a model ### Requirements - MS/PhD in Mathematics, Statistics, Computer Science, Physics, or related quantitative field - 7+ years of hands-on alpha research experience in a systematic hedge fund or prop environment - Deep understanding of: - Statistical learning and time-series modeling - Overfitting, cross-validation, and experimental design - Portfolio construction and signal interaction effects - Strong Python skills; comfortable working close to data and infrastructure - Ability to think independently and defend ideas under scrutiny ### Benefits - Significant collaboration - Direct connection between your research and capital - Compensation aligned with real impact (hence the title) - Small, elite team — no research theatre - Access to broad datasets and flexible mandate This role is for someone who wants to be paid for results, not activity. If you’ve built signals that survived contact with the market — and you want to do it at scale — let’s talk.
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