Quantitative Researcher, Systematic Equities
Quantitative Researcher, Systematic Equities
Millennium is a top tier global hedge fund with a strong commitment to leveraging market innovations in technology and data to deliver high-quality returns.
A small, collaborative, and entrepreneurial systematic investment team is seeking a strong equities quantitative researcher to join in developing new signals and strategies. This opportunity provides a dynamic and fast-paced environment with excellent opportunities for career growth.
Job Description
Quantitative Researcher as part of a small, collaborative team, with a focus on systematic equity strategies.
Preferred Location
London or Dubai preferred
Principal Responsibilities
Work alongside the Senior Portfolio Manager on processing, integration and assessing various data sources to identify uncorrelated alphas: Work and create data pipeline with multiple vendor data sets: assessing, cleaning, creating features Understand the potential prediction power from data source and identify alpha
Preferred Technical Skills
Expert in Python (KDB/Q is a plus) Proficient in modern data science tools stacks (Jupyter, pandas, numpy, sklearn) Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related STEM field from top ranked University Demonstrated knowledge of quantitative finance, mathematical modelling, statistical analysis, regression, and probability theory Excellent communication, problem-solving, and analytical skills, with the ability to quickly understand and apply complex concepts
Preferred Experience
1+ years of experience working in a systematic trading environment with a focus on equities 1+ years of experience working with multiple vendor data sets and, in particular, manipulating data (assessing, cleaning, creating features, etc.) Strong experience in evaluating alphas with statistical methods Experience collaborating effectively with cross functional teams, multitasking and adapting in a fast-paced environment
Highly Valued Relevant Experience
Strong intuition about feature/data prediction power Extremely rigorous, critical thinker, self-motivated, detail-oriented, and able to work independently in a fast-paced environment Entrepreneurial mindset Curiosity and critical thinker Eagerness to learn and grow professionally Highly organized, eager to improve and create tools in order to increase efficiency and to scale up the research effort
