Quantitative Researcher (Equities Stat-Arb High Frequency)

 

This is a rare opportunity for a Quantitative Researcher to be a foundational member of a new trading team, playing a pivotal role in building out a new high-frequency equity portfolio from the ground up. Launched by a sophisticated quantitative trading entity, you will have the autonomy and impact of a startup environment while being backed by the immense resources and data of an established leader. The firm's core is rigorous research into market anomalies, fueled by unparalleled access to a wide range of publicly available data sources, and you will be at the heart of this effort, shaping the research direction and success of this new venture from its inception.

 

As a key researcher on this new team, you will take ownership of the entire research pipeline, from generating alpha ideas to portfolio construction and performance analysis. We are looking for a creative and driven researcher, passionate about deciphering the markets through statistical analysis and machine learning, who wants to see their intellectual curiosity translate into financial outperformance.

 

• Find alphas in global equity markets by applying rigorous statistical analysis to technical or alternative data sets.
• Conduct hypothesis testing, feature design, and backtesting to discover and refine new alpha ideas.
• Manage the full research pipeline, including alpha generation, portfolio construction, back-testing, and monetization.
• Work with a new team, contributing to its growth and success in mid-frequency equity trading.

 

• At least 2 years of experience in quantitative research; experience in medium-frequency equity research is a plus
• Strong analytical and quantitative skills with solid knowledge of statistics, linear algebra, or machine learning
• Proficiency in Python and familiarity with scientific libraries such as NumPy and Pandas
• A Bachelor’s degree or higher in mathematics, statistics, computer science, or a related quantitative discipline
• Ability to work independently and collaboratively within a team