Senior Quantitative Engineer, Systematic Cross Commodity
Millennium is a global alternative investment management firm, founded in 1989, which manages more than $45 billion in assets.
Work with Python, C++, Docker, Kubernetes, Ceph, MongoDB, Kafka, Numpy, Polars, Scikitlearn, and Pytorch on a small, collaborative systematic trading team. The role involves developing real-time event-driven systems for alpha research, feature engineering, portfolio construction, and trade execution.
Free Tailor for ATS: 10/10 runs left
Senior Quantitative Engineer, Systematic Cross Commodity
Senior Quantitative Engineer, Systematic Cross Commodity
Please direct all resume submissions to QuantTalentEUR@mlp.com and reference REQ-30456 in the subject line.
Job Description
We are a small, collaborative systematic trading team based in London looking for a senior engineer to aid in the implementation and continued development of our team's core software and technical infrastructure. The role involves the development and maintenance of sophisticated tools for alpha research along with the production systems used in feature engineering, portfolio construction, and trade execution.
The ideal candidate should be an expert engineer with a deep theoretical foundation, extensive systems design experience, and significant expertise in both high-level and systems programming languages (we primarily use Python and C++) and should be motivated by the idea of playing a pivotal part in a high-impact, technology-driven business. Besides strong technical skills, we value exceptional attention to detail, a strong intuition for the pragmatism-robustness tradeoff and, most importantly, someone who works well in a close-knit, start-up-style team.
Location
London
Principal Responsibilities
Develop sophisticated research tooling to enable and accelerate alpha discovery.
Develop real-time event-driven systems for signal computation, trade-decision-making and execution.
Design, implement, and maintain the core systems and services to enable real time data ingestion, retrieval and distributed compute for both research and production.
Oversee the ongoing operation of all components within the systems landscape to ensure resilience and detect defects as they arise.
Preferred Technical Skills
Exceptional programming skills in both high-level and low-level languages (Python & C++ or similar).
Familiarity with modern distributed computing platforms (specifically: docker, kubernetes, ceph, mongodb & kafka).
Theoretical proficiency in numerical computing, online algorithms, data structures, networking, databases, and operating systems.
Familiarity with typical quantitative research toolchains including Numpy, Polars, Scikitlearn, Pytorch, etc.
DevOps: version control, testing frameworks, release processes, build systems.
Excellent communication, problem-solving, and analytical skills.
Preferred Experience
Extremely strong computer science or engineering background with 5+ years of experience.
Experience designing and implementing:
Distributed Systems.
Real-time event-driven systems.
Large-scale time series data ingress, storage and processing.
Experience with the architectural design of large-scale software systems.
Experience with systematic futures trading.
Exposure to CICD-style implementation/release methodologies with a large complex codebase.
Master’s or PhD in Computer Science, Physics, Engineering, Statistics, Applied Mathematics, or related technical field.
Additional Relevant Experience
Prior role as a quantitative developer supporting a multi-asset systematic trading business.
Experience with a broad spectrum of finance-relevant data sources (e.g. tick data, fundamental data and alternative data).
Functional understanding of foundational trading & risk management concepts.
Target Start Date
As soon as possible