Portfolio Analytics Strategy Senior Associate

Top-Tier Investment Management Firm in Midtown, Manhattan is seeking a Portfolio Analytics Strategy Senior Associate position!

Responsibilities:

• Partner closely with investment professionals to analyze portfolio performance, risk exposures, portfolio construction, and market trends while helping deliver data-driven insights that support investment decision-making, product development, client service, and asset growth.
• Transform complex data into actionable intelligence, enabling investment, risk, and distribution teams to make better-informed decisions, and will conduct analysis on assigned investment strategies/portfolios, asset class characteristics, portfolio construction, and positioning to support the needs of PMs.
• Developing and enhancing portfolio analytics for different investment vehicles within specific portfolio strategies
• Develop a strong working knowledge of all PR&DA tools available, including FactSet Portfolio Analytics (PA), MSCI Barra, Morningstar Direct, Nasdaq eVestment, Advent Portfolio Exchange (APX), and Baron proprietary tools and models.
• Conduct quantitative and qualitative analysis of performance, performance contribution and attribution, style/factor exposures, and portfolio and performance-based characteristics across strategies and peer groups.
• Serve as the dedicated analytics specialist for assigned equity strategies, developing a deep understanding of investment objectives, guidelines, holdings, performance drivers, and risk exposures.
• Support cross-functional initiatives, including product development, investor communications, and competitive positioning.
• Liaise with the Risk & Quantitative Data Analytics and Performance & Peer Analytics teams to ensure consistency and alignment in analytics delivery.

Qualifications:

• Bachelor's Degree
• 3+ years in a similar position with a fund is ideal
• Relevant experience in performance/portfolio analytics, equity research, risk/quantitative analysis, or a related function within the investment management industry.
• Proficiency with financial applications such as FactSet PA, Morningstar Direct, Nasdaq eVestment, Bloomberg, or similar platforms.
• Working knowledge of relevant programming languages (Python, SQL, R) and data visualization tools (Microsoft Power BI and/or Tableau) for data manipulation and automation.
• Ability to interpret complex investment concepts and draw actionable insights, with proficiency in financial modeling, statistical analysis, data interpretation.
• Ability to work well in a collaborative environment while also taking initiative, ownership, and responsibility for individual projects.