Millennium

Junior Business Analyst

Millennium London, England, United Kingdom

Investment Management · 5,001-10,000 employees

Yesterday
business-analyst Mid (2-5 yrs) Full-time United Kingdom
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About the role

The Junior Business Analyst will partner with quantitative research and software engineering teams to translate investment strategies into technical requirements. They will manage the end-to-end lifecycle of equity risk modeling tools and oversee the integration of quantitative models into existing infrastructure.

What they look for

SQL Python Agile Methodologies Asset Pricing Quantitative Factor Risk Modeling Portfolio Optimization Portfolio Construction Risk Management JIRA Confluence Data Analysis Prototyping Software Development Lifecycle Technical Requirements Mathematical Modeling

Requirements

Candidates must have two to five years of sell-side experience and at least two years of experience with software development lifecycles and Agile methodologies. Strong proficiency in SQL, Python, and an understanding of asset pricing and risk management workflows are required.

Full description

Junior Business Analyst

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 Core to the health and growth of Millennium’s business, the Information Technology organization develops flexible, scalable technology and advanced proprietary systems, including the next generation of analytical and trading capabilities. The team partners with portfolio risk research and technology groups to develop and enhance risk and performance platforms that support equity risk modeling, investment analytics, and trading tools.

What You'll Do

  • Partner with quantitative research and software engineering teams to translate model specifications and investment strategies into clear technical requirements
  • Manage the end-to-end requirements lifecycle for equity risk modeling and trading tools
  • Design and oversee the integration of quantitative models and datasets into existing trading and risk infrastructure
  • Perform data analysis and prototyping to validate model inputs and outputs and maintain data integrity across the research pipeline
  • Develop and maintain functional specifications, model logic documentation, data dictionaries, and documentation for quantitative tools and data feeds
  • Conduct end-user testing and feature validation to confirm solutions align with the mathematical and business intent of investment professionals and portfolio research teams
  • Conduct discovery to understand the nuances of specific asset classes and emerging technologies relevant to fundamental and quantitative investing

What You Bring

  • Two to five years of sell-side experience
  • At least two years of experience working with software development lifecycles and Agile methodologies
  • Strong understanding of asset pricing and quantitative factor risk modeling workflows, including portfolio optimization, portfolio construction, and risk management fundamentals
  • Experience working directly with portfolio researchers and software engineers
  • Strong SQL and Python skills for data analysis and prototyping
  • Experience using JIRA and Confluence
  • Excellent written and verbal communication skills, with the ability to convey complex mathematical concepts clearly to technical and nontechnical stakeholders
  • Strong analytical and problem-solving skills, with the ability to convert abstract quantitative challenges into actionable technical specifications and an interest in scaling quantitative analytics across portfolio research and enterprise risk platforms

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