We are working with a top tier buy side firm whose systematic trading team are dedicated to building a machine-driven investment pipeline that can tackle problems of scale far beyond the reach of traditional investment approaches.
We are working with a top tier buy side firm whose systematic trading team are dedicated to building a machine-driven investment pipeline that can tackle problems of scale far beyond the reach of traditional investment approaches. Even though they are operating in the financial industry, they are committed to pushing the boundary of human knowledge in related fields such as mathematics, statistics, and machine learning in order to achieve their mission. They engage with work every day motivated to learn something new about the world that has yet to be discovered (and has not been previously documented in academic literature).
They are looking for a talented quantitative researcher to join the team. Successful candidates should be capable of developing novel techniques, building unique insights, and engineering robust systems that will be used in trading strategies. The ideal candidate brings a combination of strong technical skills, a passion for creative problem solving, and an intense and wide-ranging curiosity about financial markets and human behavior.
- Use a disciplined scientific approach to develop quantitative investment models
- Develop automated investment models based on internally peer-reviewed research projects
- Develop unique insights into various datasets and share with other team members in a cooperative set-up
- Use mathematical tools to analyze and optimize monetization of forecasts
- Quantitatively measure and control the risk of a portfolio of instruments
- Apply scientific methods to improve the efficiency of a research and trading pipeline
- Masters or doctorate degree in a quantitative discipline, such as statistics, mathematics, physics, electrical engineering, computer science, or operations research
- Experience using sophisticated mathematical tools, generalizing these tools to different contexts
- Experience analyzing real world problems and large amounts of empirical data with a disciplined scientific approach
- Capable of pursuing the application of machine learning and advanced statistical techniques
- Strong written and verbal communication skills, especially on technical subjects
- Curiosity driven mindset with ability to explore uncharted territory
- Highly motivated and willing to take ownership of work
- Familiarity in at least one programming language (C++ and Python preferred)
- Maximum of ~5 years of experience in the financial industry is preferred, but not required