Our client is seeking a highly analytical and detail-oriented Senior Associate, Quant & Data Science to join their Portfolio Analytics Group. In this pivotal role, you will sit at the intersection of data science, quantitative finance, and portfolio analytics—developing tools and frameworks that power investment decisions across a global, multi-asset class portfolio.

Responsibilities:

• Develop and automate valuation and return calculations for a global multi-asset class portfolio.
• Build performance attribution frameworks to uncover the drivers of returns across asset classes.
• Design and maintain quantitative models to manage market, liquidity, and portfolio risks—spanning both liquid and illiquid assets.
• Translate Excel-based models into scalable, programmatic solutions.
• Be a self-starter eager to dive into diverse asset classes and build tools that deliver a unified view of portfolio performance across the enterprise.
  

Requirements:

• Practical experience in a finance-oriented, fast-paced environment.
• A strong ability to dissect ambiguous problems and apply the right analytical techniques.
• High proficiency in data extraction, data cleansing, and quantitative analysis.
• Deep experience with quantitative modeling and data science in financial contexts.
• A degree in a quantitative field (e.g., Mathematics, Statistics, Engineering, Computer Science, Financial Engineering).
• Expertise in Python and key data science libraries (Pandas, NumPy, SciPy, Scikit-learn, Matplotlib, etc.).
• Experience in financial/investment analysis is essential.
• Bonus: Experience with other languages (e.g., R, SQL, Julia).

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