Quantitative Developer, Systematic Equities

Millennium Management LLC, City of Westminster

Quantitative Developer, Systematic Equities

Salary Not Specified

Millennium Management LLC, City of Westminster

  • Full time
  • Permanent
  • Onsite working

Posted today, 4 Oct | Get your application in now to be one of the first to apply.

Closing date: Closing date not specified

job Ref: 8d9b1e5b9c264c72b3ca3bf9c28c4c91

Full Job Description

Job Description: Quantitative Developer, Systematic Equities
Maximise your chances of a successful application to this job by ensuring your CV and skills are a good match.

Please send resume submissions to and reference REQ-19460 in the subject line.

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 an experienced developer to join in building critical trading infrastructure. This opportunity provides a dynamic and fast-paced environment with excellent opportunities for career growth.

Location: London

Principal Responsibilities
1. Partner closely with the Portfolio Manager to develop data engineering and prediction tools primarily for the systematic trading of equities.
2. Develop software engineering solutions for quantitative research and trading
+ Assist in designing, coding, and maintaining tools for the systematic trading infrastructure of the team.
+ Build and maintain robust data pipelines and databases that ingest and transform large amounts of data.
+ Develop processes that validate the integrity of the data.
3. Implementation and operation of systems to enable quantitative research (i.e., large scale computation and serialization frameworks)
+ Live operation of such systems, including monitoring and pro-active detection of potential problems and intervention.
4. Stay current on state-of-the-art technologies and tools including technical libraries, computing environments, and academic research.
5. Collaborate with the PM and the trading group in a transparent environment, engaging with the whole investment process.

Preferred Technical Skills
1. Master's or PhD in Computer Science, Physics, Engineering, Statistics, Applied Mathematics, or related technical field appropriate to a computational background.
2. Expert in C++.
3. Advanced programming skills in Python.
4. Strong Linux-based development.

Preferred Experience
1. Extremely strong computer science or engineering background with 3+ years of experience.
2. Approx. 3-4 years of professional experience in a computer science/computational role.
3. Experience working in a technical environment with DevOps functions (Google Cloud, Airflow, InfluxDB, Grafana).
4. Design and implementation of front-office systems for quant trading.

Highly Valued Relevant Experience
1. Knowledge of machine learning and statistical techniques and related libraries.
2. Experience as a quantitative developer supporting an intraday (or faster) system.
3. Experience with the development practices of large tech (Google/Meta, etc.) or finance firms.
4. Experience with financial data.

Target Start Date: As soon as possible

1. Master's or PhD in Computer Science, Physics, Engineering, Statistics, Applied Mathematics, or related technical field appropriate to a computational background.
2. Expert in C++.
3. Advanced programming skills in Python.
4. Strong Linux-based development.

Preferred Experience
1. Extremely strong computer science or engineering background with 3+ years of experience.
2. Approx. 3-4 years of professional experience in a computer science/computational role.
3. Experience working in a technical environment with DevOps functions (Google Cloud, Airflow, InfluxDB, Grafana).
4. Design and implementation of front-office systems for quant trading.

Highly Valued Relevant Experience
1. Knowledge of machine learning and statistical techniques and related libraries.
2. Experience as a quantitative developer supporting an intraday (or faster) system.
3. Experience with the development practices of large tech (Google/Meta, etc.) or finance firms.
4. Experience with financial data.