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About The Role

We seek a Senior Quantitative Strategist with deep expertise in multi-factor models, portfolio construction, trading strategies, and portfolio optimization. A CFA or strong financial background in investments or accounting and an advanced degree in a quantitative field are preferred. The ideal candidate has significant experience with portfolio and performance attribution analysis, S&P Global’s ClariFi, and coding proficiency in Python, C++, or similar languages. Familiarity with risk systems, AI, and ML techniques is beneficial.

Driving initiatives, developing quantitative products, managing data, and collaborating with engineers, data scientists, and product managers to enhance modeling methodologies and strategies. A CFA or strong financial background is preferred.

• Deep domain experience in a quantitative investment role focusing on multi factor models, portfolio construction, implementation and analysis of trading strategies and portfolio optimization techniques.
• CFA preferred or strong financial background in investments or accounting
• Advanced degree in a quantitative field.
• Significant and extensive experience with portfolio and performance attribution analysis, proficient in analyzing portfolio returns to evaluate the influence of different factors and strategies, facilitating informed decision-making and strategy enhancement.
• A must - significant experience with S&P Global’s backtesting tool, ClariFi.
• Knowledge of risk systems is a plus (S&P Global, Factset, MSCI RiskMetrics, Barra, Bloomberg PORT).
• Experience generating technical specifications for backend and frontend developers.
• Preferably strong knowledge of AI and ML techniques.
• Coding proficiency in Python, C++, or another compiled language.
• Experience in driving initiatives from ideation to delivery by collaborating with quant team members, data team members, and engineering teams.
• Prior experience building quantitative products at a Tier 1 buy or sell side firm or data vendor.
• Experience with developing or implementing scenario shocks and hedge construction.
• Experience with risk Model Analytics.
• Strong technical understanding of cloud/enterprise infrastructure, RESTful APIs, etc.)
• Experience with the management and usage of multi-asset, alternative and proprietary data in sectors or asset classes.
• Deep knowledge of use cases across buy and sell side, asset classes, and different trading strategies.
• Experience with the management and usage of multi-asset, alternative and proprietary data in finance.
• Maintain and develop proprietary equity models.
• Utilize data sets and analytics from the larger organization to incorporate into quant models
• Strategize and develop new modeling methodologies, processes, and strategies.
• Ability to effectively communicate and collaborate with Engineers, UX, Data Scientists,