SIG’s Quantitative Research Associates hold advanced degrees from diverse fields including mathematics, physics, computer science, and engineering. Our quants apply their problem solving expertise to real-time trading opportunities within the capital markets.
At SIG, you will work alongside traders and software engineers to develop, test, and implement predictive models, pricing models, and technical tools. You will utilize your quantitative ability and technical skill set to design strategies essential to SIG’s trading performance.
You will attend classes taught by experienced traders to learn about capital markets, decision science, and game theory. This theoretical training is reinforced through mentoring provided by successful quants at SIG who will help you bridge the gap between your academic experience and the trading world.
The goal of our 10-week summer programprogramme is to give you real-world working experiences that apply quantitative research to the firm’s trading activity. You will work on essential projects for the firm while gaining a better understanding of how we approach the markets.
Our quant interns participate in educational programsprogrammes customized to their unique position at SIG. Classes provide an introduction to the products SIG trades and the finance industry. They evolve into challenging quantitative courses that expose the application of quantitative theory to real-world problems that we face as contributors to the US open markets. Interns are also mentored by a Quantitative Researcher at SIG while spending time on our trade floor gaining hands-on experience. The education programprogramme is designed to advance knowledge of our business, current industry topics, and the application of quantitative theories in finance.
Like earning a doctorate, a successful career at SIG requires a relentless pursuit of knowledge, creative thinking, and extraordinary attention to detail.
As a PhD at SIG, you will work in an environment which is challenging, fast-paced, and competitive. Whether the application is time series modelling or reinforcement learning, you will apply academic rigor to transform your research into concrete results work with state-of-art techniques in statistics and optimisation. Success at SIG relies on both a strong technical foundation and effective collaboration between our quantitative researchers, technologists, and traders. New hires will start working right away on a project in proprietary trading, with the guidance and mentorship of a senior member of our team.
Quantitative Researchers are dedicated to the data-driven development and improvement of our trading models at SIG. Our Quantitative Researchers apply their problem-solving skills and mathematical creativity to create solutions in today’s competitive and constantly changing financial markets. In this role, you will be highly involved in the day-to-day discussions that shape our trading activities and transform quantitative methods into trading opportunities. Machine Learning Engineers design, develop, and deploy algorithms used to optimise SIG’s trading activities. You will join a team of engineers and researchers who specialise in the application of machine learning techniques to the modelling and trading of financial instruments. Combining cutting-edge research with real industry data, our Machine Learning Engineers build tools that directly impact the financial markets.
At SIG, you will work alongside traders and technologists to develop, test, and implement predictive models, pricing models, and technical tools. You will utilise your quantitative ability and technical skill set to design strategies essential to SIG’s trading performance.
You will attend classes taught by experienced traders to learn about capital markets, decision science, and game theory. This theoretical training is reinforced through mentoring provided by successful quants at SIG who will help you bridge the gap between your academic experience and the trading world. Our Quantitative Researchers have an opportunity to spend time learning & working in US offices as part of the graduate program.
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