Senior Quantitative Researcher, Systematic Equities

Millennium Management; London; On-site; GBP 80,000 - 100,000; Full time

Job description

Senior 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

We are seeking a senior quantitative researcher to partner with the Senior Portfolio Manager to create alpha from various data sources for the systematic trading of global equity strategies.

Preferred Location

London or Dubai preferred

Principal Responsibilities

1. Work alongside the Senior Portfolio Manager on building alpha research pipelines:
1. Understand the potential prediction power from data sources and identify alphas.
2. Identify and process datasets to create features or alphas.
3. Perform various statistical analyses to ensure robustness.
2. Mentor and guide junior team members.

Preferred Technical Skills

1. Expert in Python (KDB/Q is a plus).
2. Proficient in modern data science tool stacks (Jupyter, pandas, numpy, sklearn).
3. Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related STEM field from a top-ranked university.
4. Demonstrated knowledge of quantitative finance, mathematical modeling, statistical analysis, regression, and probability theory.
5. Excellent communication, problem-solving, and analytical skills, with the ability to quickly understand and apply complex concepts.

Preferred Experience

1. 4+ years of experience working in a systematic trading environment with a focus on equities.
2. 4+ years of hands-on experience working with multiple vendor datasets and, in particular, manipulating data (assessing, cleaning, creating features, etc.).
3. Demonstrated success in building uncorrelated alphas and in adding orthogonal value to portfolios.
4. Established alpha research pipeline with production-grade output.
5. The ideal candidate would have a few years of successful live trading history.
6. Strong experience in evaluating alphas with statistical methods.
7. Experience collaborating effectively with cross-functional teams, multitasking, and adapting in a fast-paced environment.

Highly Valued Relevant Experience

1. Strong intuition about feature/data prediction power.
2. Extremely rigorous, critical thinker, self-motivated, detail-oriented, and able to work independently in a fast-paced environment.
3. Entrepreneurial mindset.
4. Curiosity and critical thinking.
5. Eagerness to learn and grow professionally.
6. Highly organized, eager to improve, and create tools to increase efficiency and scale up research efforts.