Quantitative Researcher (Equities)
Fintal Partners, New York, NY, United States
We’re partnering with a leading global trading firm that is actively building out its equities capabilities. This is a unique opportunity to join a growing, high-impact team focused on developing next-generation systematic trading strategies at the intersection of equities and derivatives.
The team is focused on combining expertise with predictive signals leveraging large-scale data and advanced modeling to drive trading decisions in highly automated, low-latency environments.
This is a role for someone who wants to do more than just research as you’ll have direct visibility into how ideas move from concept to production to PnL.
What You’ll Be Doing
Analyze large, complex datasets to identify predictive signals in equity markets
Develop and refine systematic trading strategies across equities
Work closely with engineering to design and improve research and production frameworks
Rapidly prototype and test new ideas (primarily in Python)
Take ownership of the full lifecycle from research to live deployment
Continuously enhance and expand existing models to unlock new sources of alpha
What They’re Looking For
3+ years of experience in a quantitative research role within systematic trading
Strong background in equity signal generation and predictive modeling
Experience working with high-frequency or intraday strategies is highly relevant
Proficiency in Python for research and prototyping
Strong academic background in a quantitative field (e.g., mathematics, physics, computer science, financial engineering)
Exposure to automated trading environments or market making systems is a plus
Why This Role
High ownership:
Direct impact on trading outcomes, not siloed research
Collaborative environment:
Tight feedback loop between research, engineering, and trading
Strong infrastructure:
Ability to scale ideas quickly into production
Growth:
Join a team in build mode, not maintenance mode
#J-18808-Ljbffr
The team is focused on combining expertise with predictive signals leveraging large-scale data and advanced modeling to drive trading decisions in highly automated, low-latency environments.
This is a role for someone who wants to do more than just research as you’ll have direct visibility into how ideas move from concept to production to PnL.
What You’ll Be Doing
Analyze large, complex datasets to identify predictive signals in equity markets
Develop and refine systematic trading strategies across equities
Work closely with engineering to design and improve research and production frameworks
Rapidly prototype and test new ideas (primarily in Python)
Take ownership of the full lifecycle from research to live deployment
Continuously enhance and expand existing models to unlock new sources of alpha
What They’re Looking For
3+ years of experience in a quantitative research role within systematic trading
Strong background in equity signal generation and predictive modeling
Experience working with high-frequency or intraday strategies is highly relevant
Proficiency in Python for research and prototyping
Strong academic background in a quantitative field (e.g., mathematics, physics, computer science, financial engineering)
Exposure to automated trading environments or market making systems is a plus
Why This Role
High ownership:
Direct impact on trading outcomes, not siloed research
Collaborative environment:
Tight feedback loop between research, engineering, and trading
Strong infrastructure:
Ability to scale ideas quickly into production
Growth:
Join a team in build mode, not maintenance mode
#J-18808-Ljbffr