Quantitative Portfolio Management Associate - Top Alternatives Firm NYC Job at Coda Search│Staffing, New York, NY

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  • Coda Search│Staffing
  • New York, NY

Job Description

We are currently partnered with the Insurance arm of a top alternative asset manager looking to bring on a Quantitative Portfolio Management Associate to their team. The firm is know for having an elite global brand and supporting their growth within all their alternatives business lines.

This role is integral to portfolio construction, asset allocation, and portfolio optimization efforts, leveraging advanced quantitative techniques to drive investment decision-making. The successful candidate will play a key role in developing and implementing analytical models, working with large datasets, and providing insights that enhance portfolio efficiency and risk-adjusted returns. This position offers an opportunity to work closely with PMs, risk, and other senior investment professionals across multiple asset classes, mainly fixed income and equities but also exposure to private equity, private credit, and real estate.

Key Responsibilities:

  • Design and implement quantitative models for portfolio construction, optimization, and asset allocation.
  • Conduct in-depth portfolio analytics, including stress testing, factor analysis, and risk decomposition.
  • Develop and maintain Python- and SQL-based analytical tools to support investment decisions.
  • Collaborate with portfolio managers and research teams to integrate quantitative insights into the investment process.
  • Analyze and interpret large-scale financial datasets to extract actionable investment insights.
  • Work on multi-asset class portfolio strategies, including public and private market investments.
  • Present findings to senior leadership and contribute to strategic decision-making.

Qualifications:

  • 3-7 years of experience in a quantitative investment role, preferably within an asset management, hedge fund, or investment advisory setting.
  • Advanced degree (Master’s or PhD preferred) in Quantitative Finance, Financial Engineering, Applied Mathematics, Computer Science, or a related field.
  • Strong programming skills in Python (NumPy, Pandas, SciPy) and SQL for data extraction, analysis, and model implementation.
  • Experience with portfolio optimization, factor modeling, and risk analytics.
  • Solid understanding of multi-asset class investing, including private markets.
  • Ability to work with large datasets and apply statistical techniques and machine learning where applicable.
  • Excellent problem-solving skills and ability to communicate complex quantitative concepts to non-technical stakeholders.
  • CFA certification is a plus.

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