About Millennium
Millennium is a global, diversified alternative investment firm, founded in 1989. Defined by evolution, innovation and focus, Millennium’s mission is to deliver results for our investors.
Our people are empowered with both independence and support: the autonomy to pursue ideas with conviction and the backing of a global network committed to collaboration, disciplined risk management and continuous learning. With opportunities to deepen expertise and accelerate development, talent at Millennium is equipped to adapt, evolve and build lasting impact over time. Discover how transformative growth accelerates impact.
Meet the Team
The Systematic Data Group is building a world class systematic data platform, which will power the next generation of systematic portfolio engineers. We are looking for exceptional talents to join our growing data platform team. The team consists of content specialists, data scientists, data analysts, data operations analysts and engineers who are responsible for discovering, maintaining and analyzing sources of alpha for our portfolio managers.
This is an opportunity for individuals who are passionate about quantitative investing. The role builds on individual’s knowledge and skills in four key areas of quantitative investing: data, statistics, technology and financial markets.
What You'll Do
- Support the onboarding, validation, and maintenance of internal and external datasets used across systematic investment workflows
- Perform data quality checks, exception handling, reconciliation, and root-cause analysis
- Generate descriptive statistics, data summaries, coverage reports, and quality metrics to help users understand dataset characteristics
- Maintain metadata, tagging, documentation, data dictionaries, and operational runbooks for datasets and workflows
- Work with vendors and brokers to understand data characteristics, formats, definitions and quality issues
- Partner with portfolio managers to support dataset usage, data recommendation and resolve trading critical data-related issues
- Help improve operational processes by identifying automation opportunities, workflow enhancements, and monitoring improvements
- Monitor daily data pipelines, investigate issues, and coordinate timely resolution with engineering, vendors, and internal stakeholders
What You Bring
- Bachelor’s, Master’s, or Ph.D.in Computer Science, Mathematics, Statistics or other field requiring quantitative analysis
- Recent graduates are welcome, as are candidates with up to 6 years of experience in data operations, data analytics, financial data, technology, or financial services
- Strong programming skills in Python; experience with Go, Rust, R, Java, C#, or C++ is a plus
- Strong SQL skills, including experience with SQL, PL/SQL, T-SQL, or similar relational database technologies
- Strong analytical and problem-solving skills, with high attention to detail and ability to investigate data issues
- Strong written and verbal communication skills, with the ability to collaborate across technical and business teams
- Solid understanding of financial data concepts, including standards, types, data lineage, normalization, and data quality