Portfolio Analytics Specialist

[Hong Kong]

Arcana is a portfolio intelligence platform used by hedge funds and asset managers to analyze performance and risk. We’re rethinking the tools institutional investors rely on—and we’re hiring analysts who want to drive that transformation.

This isn’t a typical modeling-and-memos analyst role. Our analysts work directly with product, engineering, and data science to shape institutional-grade financial software. If you’re an analyst looking for more impact, more ownership, and the chance to help shape real tools for investors—we’d love to talk.

Responsibilities

• Collaborate with product, engineering, and data science teams to build robust portfolio intelligence tools and analytics components
• Analyze portfolio- and security-level performance, risk, and attribution
• Decompose returns to identify key drivers of alpha, beta, and idiosyncratic outcomes
• Conduct market, macroeconomic, and security-level research to support client workflows and product insights
• Validate, interpret, and clearly communicate financial metrics to both internal stakeholders and clients

Requirements

• 2–4+ years of experience in a front-office financial role (investment banking, hedge fund, asset management, or similar)
• Exceptional analytical and Excel skills, with strong proficiency in financial modeling and interpreting large datasets
• Deep understanding of core investment concepts: portfolio theory, risk attribution, yield, drawdown, correlation, and volatility
• Excellent at communicating with institutional clients—including portfolio managers, analysts, CIOs, and risk managers—with the ability to distill complex analysis into clear, actionable insights
• Demonstrated deep interest in financial markets, investment strategies, and institutional workflows
• Self-starter with the ability to work independently in a fast-paced, remote environment
• Familiarity with institutional investment processes, research platforms, and financial data tools

Qualifications

• Bachelor’s or Master’s degree from a top-ranked university in Finance, Economics, Engineering, or a related field
• First-Class Honours degree (or international equivalent) required
• CFA, FRM, or MBA is a strong plus
• Experience with tools like Bloomberg, FactSet, or data programming languages (Python, R) is a bonus