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Portfolio Analytics Specialist

Listing for: arcanaanalytics
Full Time position Listed on 2026-11-14
Job specializations:
Salary/Wage Range or Industry Benchmark: 90000 - 140000 USD Yearly USD 90000.00 140000.00 YEAR

Job Description & How to Apply Below

Role overview

An analyst role embedded in a portfolio intelligence platform built for hedge funds and asset managers. Rather than producing memos in isolation, the analyst partners directly with product, engineering, and data science colleagues to shape institutional-grade financial software used by professional investors.

Responsibilities
  • Collaborate with product, engineering, and data science teams to build portfolio intelligence tools and analytics components
  • Analyze portfolio- and security-level performance, risk, and attribution
  • Decompose returns to identify 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 institutional clients
Requirements
  • 2 to 4+ years of experience in a front-office financial role such as investment banking, hedge fund, or asset management
  • Strong analytical and Excel skills, with proven proficiency in financial modeling and interpreting large datasets
  • Deep understanding of portfolio theory, risk attribution, yield, drawdown, correlation, and volatility
  • Excellent communication with institutional audiences, including portfolio managers, analysts, CIOs, and risk managers
  • Bachelor's or Master's degree from a top-ranked university in Finance, Economics, Engineering, or a related field, with a First-Class Honours degree or international equivalent required
  • Self-starter mindset suited to working independently in a fast-paced, remote environment
Nice to have
  • CFA, FRM, or MBA designation
  • Familiarity with institutional research platforms such as Bloomberg or Fact Set
  • Experience with data programming languages such as Python or R
  • Familiarity with institutional investment processes and financial data tools
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