Associate Portfolio Analytics Strategy Specialist

Overview

• Drive portfolio analytics and strategy development, delivering actionable insights to enhance investment decisions and optimize performance outcomes.
• Collaborate with cross-functional teams to support portfolio construction and strategic initiatives across diverse investment vehicles.
• Transform complex data into meaningful analysis, aiding portfolio managers in achieving investment objectives.
• Develop and refine analytics tools and reporting frameworks to streamline workflows and improve decision-making.
• Conduct quantitative and qualitative analysis of portfolio performance, exposures, and characteristics.
• Prepare comprehensive materials and summaries for client reviews and internal strategy discussions.
• Contribute to firm-wide strategic initiatives by leveraging analytics expertise and insights.
• Support innovation and continuous improvement in portfolio analytics methodologies and practices.

Key Responsibilities & Duties

• Serve as the analytics specialist for assigned equity strategies, ensuring alignment with investment objectives and risk guidelines.
• Conduct detailed quantitative analysis of performance attribution, style factors, and risk exposures.
• Develop dashboards, reports, and presentations for stakeholders, enhancing transparency and communication.
• Collaborate with investment, risk, and client-facing teams to support product development and investor communications.
• Enhance reporting processes by implementing best practices and innovative analytics solutions.
• Mentor junior associates, fostering skill development and ensuring high-quality deliverables.
• Investigate performance-related issues, ensuring data accuracy and reliability across analytics tools.
• Support strategic decision-making through comprehensive analysis and actionable recommendations.

Job Requirements

• Bachelor's degree in business, finance, statistics, engineering, or a related quantitative field.
• 3-6 years of experience in portfolio analytics, equity research, or risk analysis.
• Proficiency in financial applications such as FactSet PA, Morningstar Direct, and Bloomberg.
• Knowledge of programming languages like Python, SQL, or R for data manipulation and analysis.
• Strong analytical skills with expertise in financial modeling and statistical analysis.
• Exceptional communication skills to present complex concepts effectively to diverse audiences.
• Advanced proficiency in Microsoft Excel, VBA, PowerPoint, and Word.
• Highly proactive, self-motivated, and committed to continuous learning and professional development.