Overview
SIG is seeking a Software Developer to our Options trading desk. In this role, you will work closely with our Quantitative Researchers and Strategists to grow and scale our signal generation platform which is critical to our strategy development process.
Performance is key for our high-frequency trading environment. We're looking for an engineer with significant C++ and Python experience who has a deep appreciation for performance.
In this role, you will:
• Design, develop, and scale our signal generation platform using your knowledge of object-oriented programming and C++/Linux and Python
• Partner with Quantitative Researchers and Strategy Developers to engage in problem definition, decomposition, and identify new development areas in order to evolve our signal generation technology
• Analyze user needs and software requirements to determine feasibility of design within time and performance constraints
What you can expect from us:
Real Impact: By integrating sophisticated coding techniques with innovative engineering ideas, we design and optimize systems that can process massive amounts of data while still ensuring high performance and stability. You'll see how your contributions towards developing and supporting leading-edge hardware and software technologies make a firm-wide impact that makes us all smarter, faster, and better.
Collaboration: You will partner closely with our Strategy Developers and Quantitative Researchers to translate complex trading problems into scalable and highly performant hardware solutions.
Growth: For many of our roles, 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.
Benefits: SIG offers a wide array of competitive employee perks & benefits.
What we're looking for
• At least 6+ years of experience in C++, developing software with strict performance requirements
• Possess a deep appreciation for performance and benchmarking. You have experience in large scale computing problems and understand performance trade-offs!
• Strong systems fundamentals (virtual memory, numa, io, networking, etc.)
• Deep Linux knowledge and strong systems fundamentals
• Experience in Python data analysis and/or low level Python
• Strong understanding of data structures and algorithms
• Experience building large scale data transformation pipelines
• Bachelor's degree in Computer Science, Engineering, Mathematics or related discipline or its foreign equivalent; advanced degree is preferred
Nice to Have:
• Experience working in a HFT environment
• Enthusiasm for working with data, especially large sets of data, automating operations. Good aesthetics for cleanliness and correctness in data
• Windows development platform experience a plus
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.
SIG does not accept unsolicited resumes from recruiters or search firms. Any resume or referral submitted in the absence of a signed agreement will become the property of SIG and no fee will be paid.
