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Quantitative Researcher, Equity Stat Arb

Selby JenningsManhattan, NY🇺🇸United StatesPosted Oct 14, 2026

Why This Role Stands Out

This hybrid role offers exceptional mentorship and a clear path for career growth, allowing you to develop cutting-edge mid-frequency trading strategies using advanced statistical and machine learning techniques on global equity markets. You'll thrive here if you have a PhD and a passion for analyzing massive datasets, collaborating with a respected team, and contributing to a consistently profitable trading desk. Seize this unique chance to refine your quantitative research skills and build a rewarding career in a supportive environment.

Quick Overview

Seniority
Mid Senior
Employment type
Full Time
Work mode
Hybrid
Location
Manhattan, NY, United States
Posted
5 days ago
Machine LearningC++Python

Job Description

A Senior Quantitative PM focused on Equity Stat Arb strategies is looking for an Equity QR to join their team in NYC. The PM is specifically looking for someone with a PhD background (ideally with 2-4 years of buyside QR experience but will entertain exceptional PhD/Postdoc candidates from academia) who they can mentor and entrust with mid-frequency signal/strategy development on global equity markets (US equities primarily).

The hiring manager has built a name for himself in the industry after 15+ years of managing portfolios and succesfully mentoring QRs early on in their career. The incoming QR will analyze massive datasets using statistical and machine learning methods to identify + combine alpha signals with holding periods on the scale of days-to-weeks horizons.

This is a unique opportunity for those looking for a PM with a stable, consistently profitable track-record who also finds enjoyment in equipping QRs early on in their career with a rigorous, proven approach in developing stat arb trading strategies.

The ideal candidate for this role will have:

  • 2-4 years of buyside equity stat arb experience (will entertain exceptional candidates that are more junior)
  • Strong fundamental skillset in statistical + machine learning modeling
  • Experience working with large, complex datasets
  • Exceptional problem solving and modeling capabilities
  • Strong Python or C++ experience
  • Enjoys working in a collaborative team

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