Quantitative Developer, Systematic US Equity Options (Seattle)

Quantitative Developer, Systematic US Equity Options

Join to apply for the Quantitative Developer, Systematic US Equity Options role at Millennium
Quantitative Developer, Systematic US Equity Options

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Please direct all resume submissions to [email protected] and reference REQ-25564 in the subject.

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.

Job Description

Quantitative Developer/Engineer as part of a portfolio-management team primarily based in Zug, with a focus on systematic trading opportunities in US equity options. The primary focus of the developer/engineer will be on the development and subsequent optimization of infrastructure supporting the overall development and production of quantitative trading models. The ideal candidate will work directly with the quantitative researcher(s) and senior portfolio manager.

This team member will be responsible for the implementation of technology to enable large-scale computational efforts in quantitative research, as well as related efforts, such as the preparation and transformation of data and other operational tasks. This role will work with senior technologists on the design and implementation of systems, and work closely with the quantitative research team to enable their mission. The successful candidate is expecting to put in an intense effort to be an early and pivotal part of the success of a quantitative trading group.

Location

Seattle, WA

Principal Responsibilities
• Partner closely with the Senior Portfolio Manager to develop data engineering and prediction tools primarily for the systematic trading of US equity options
• 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
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
Stay current on state-of-the-art technologies and tools including technical libraries, computing environments and academic researchCollaborate with the SPM and the trading group in a transparent environment, engaging with the whole investment process
Preferred Technical Skills
• Masters or PhD in Computer Science, Physics, Engineering, Statistics, Applied Mathematics, or related technical field appropriate to a computational background
• Expert in C++
• Advanced programming skills in Python
• Strong Linux-based development

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

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

Target Start Date
• As soon as possible
Seniority level
• Seniority levelMid-Senior level
Employment type
• Employment typeFull-time
Job function
• Job functionFinance and Sales
• IndustriesInvestment Management

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