C++ Developer | Trading Strategies | Experienced Hire

SIG Susquehanna; Northern (KY); Hybrid; USD 140,000 - 190,000; Full time

Job summary

SIG Susquehanna seeks engineers for a computational role at the intersection of data analysis and high-performance computing. You will partner with quants and traders to translate strategy ideas into production systems, working on large-scale data and fast, robust infrastructure.

Ideal candidates have 3+ years in C++ development, experience with distributed systems, and a strong numeric/HPC background. A CS/Math degree is required, with advanced degrees preferred.

Qualifications

• 3+ years of experience developing performance-sensitive code in C++.
• Experience with distributed systems and microservice architectures.
• Strong numerical programming or HPC experience.
• Experience with Python or C# is a plus.
• Bachelor's degree in CS, Mathematics, or closely related field; advanced degrees preferred.

Responsibilities

• Enhance alpha generation and improve strategy and research infrastructure.
• Work with large-scale data to understand market dynamics and uncover signals.
• Collaborate with quants and traders to translate ideas into production systems.
• Apply performance-sensitive engineering practices to build fast, robust systems.

Skills

C++ development

Distributed systems

HPC

Python

C#

Education

Bachelor's degree in Computer Science or Mathematics

Job description

Overview

Susquehanna is seeking talented engineers to join our Strategy Development team in a computationally intensive role at the intersection of data analysis and high-performance engineering.

In this role, you'll work on the front lines of the business, partnering directly with quants and traders to enhance, refine, and evolve trading strategies. Our short development cycles mean strategy ideas move quickly from concept into production, and your impact is immediate and visible. You'll join a non-siloed, collaborative team of scientists and engineers with strong academic and professional track records, tackling some of the most challenging problems in trading.

What You’ll Do

• Enhance alpha generation and improve our strategy and research infrastructure
• Work with tens of petabytes of raw and well-prepped data — full tick market data, strategy decisions, fundamentals, and more — to understand market dynamics and uncover new signals
• Partner closely with quants and traders to translate strategy ideas into production systems through rapid development cycles
• Apply strong performance-sensitive engineering practices to build systems that are both fast and robust

What we're looking for

• 3+ years of progressive industry experience developing performance-sensitive code in C++
• Experience with distributed systems and microservice architecture
• Strong numerical programming or HPC experience
• Experience with C# or Python is a plus
• Bachelor's degree in Computer Science, Mathematics, or a closely related discipline (Master's or PhD preferred)

AboutSusquehanna

Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries 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.