Susquehanna International Group, LLP

Quantitative Researcher- Professional

Job Locations US-PA-Bala Cynwyd (Philadelphia Area)
Requisition ID
2024-8124
Experience Level
Experienced Professionals
Job Categories
Quantitative Research

Overview

Our Quantitative Researchers apply mathematics, statistics, and programming to find solutions to complex problems that occur in financial markets. They use research as a tool to better understand global markets, varying products, and the network of exchanges that we trade on. Quants move SIG's business forward by improving, identifying, and implementing trading strategies for the firm.

 

We don’t expect you to have prior industry experience in proprietary trading or financial services to succeed at Susquehanna International Group. We’re looking for people who are naturally curious, relentless problem solvers, and have the desire to continuously innovate, learn, and grow.

What we’re looking for

  • Ph D. or equivalent degree in Mathematics, Physics, Statistics, Electrical Engineering, Computer Science, Operations Research, or related discipline.
  • Foundational knowledge of probability and statistics (a theoretical understanding as you will be spending much of your time modeling various financial problems).
  • Experience working with and drawing conclusions from large datasets is a must.
  • Building statistical forecasting models to impact real-time problem sets and drive insight to relevant markets.
  • Strong practical computing skills in object-oriented languages.
  • Creatively and drive to challenge standard methods and come up with innovative new approaches.
  • Having a proficiency in coding cleanly and efficiently is a plus (python preferred).  
  • Previous finance industry experience is not required, but a passion for financial problem sets with real time impact is crucial.  

What you can expect from us:

  • A flat structure of collaborative environment of highly technical colleagues with a fierce passion for what they do.
  • Industry-leading resources and technology infrastructure from one of the largest proprietary trading firms to support your day-to-day mandates.
  • Extensive training, learning, development programs led by some of the top performers in the firm.
  • Tangible mentorship and cross-collaboration between trading, research, and development teams fostering an environment of openness and knowledge sharing

 

Real Impact: Solve complex technical challenges, working alongside other quantitative researchers and collaborating with traders to solve some of the most challenging research problems with real-time impact. Increased competence of technical skills and see how your contributions drive insight to markets and influence trading decisions making a firm-wide impact that makes us all smarter, faster, and better every day.

 

Balanced, Collaborative Working Culture: Our non-hierarchical culture allows employees of every level to thrive together regardless of title or tenure at SIG. With industry-leading work/life balance and a casual office environment, we’re focused on continuous development of our people in a way that works for them professionally and personally.

 

 

About SIG

SIG is a global quantitative trading firm founded by a group of friends who share a passion for game theory and probabilistic thinking. We have incorporated this approach into our culture, where you will find relentless problem solvers within each of our core disciplines: Trading, Technology, and Quantitative Research. From offices around the world, our employees collaborate to make optimal decisions and are driven by the desire to achieve winning results together. 

 

What we do

We are experts in trading essentially all listed financial products and asset classes, with a focus on derivatives trading. Through market making and market taking, we handle millions of trading transactions around the world every day, providing liquidity and ensuring competitive prices for buyers and sellers. While our presence in the market is broad, our trading desks are highly specialized, allowing for a deep understanding of unique drivers of each asset class.

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