Portfolio Analytics Specialist

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