General StrategistSusquehanna International Group, Sydney, AustraliaOverviewSIG is looking for a General Strategist. In this role, you will work with traders, quants, and software developers in a highly integrated multi-disciplinary team developing and deploying automated trading strategies. This team researches, implements, tests, deploys, and monitors proprietary systems trading across multiple markets and financial products. They work at all levels of the problem domain from market data handlers through trade monitoring. This is a very 'hands-on' position where you will be involved in idea generation and strategy production.What we're looking forWhat 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 traders, quants, and software developers to deliver and manage scalable and highly performant systems to support trading in the region and globally.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.What we're looking for:The quantitative ability to build models for asset price prediction at high and medium frequencies;The technical skill to build prototype implementations of both the model and resulting trading strategy;The experience in financial markets to analyze the resulting trades, and to understand latency and feasibility of the strategy in the market;The communication skills to explain clearly your ideas and results to the rest of the team. This will require working with C++ and/or Python systems to extract the data you will require.Job requirements:M.S./Ph.D. in Computer Science/Statistics/Math or equivalent experience.Several years' experience in financial markets and ability to recognize/understand trading opportunities.Able to work well in a team environment and produce studies for peer review.Experience in modeling (familiar with Statistical/Data Analysis/Machine learning techniques).Comfortable programming C++ and Python in a Linux environment.Able to develop prototype strategies in a large existing C++ code base.Experience with Big Data.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.Equal Opportunity Statement:We encourage applications from candidates from all backgrounds, and we welcome requests for reasonable adjustments during the recruitment process to ensure that you can best demonstrate your abilities.Susquehanna 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 Susquehanna and no fee will be paid.
#J-18808-Ljbffr
