Portfolio Analytics Associate

Overview

• Contribute to portfolio analytics for evergreen and single asset investments, driving strategic decision-making through advanced data analysis and financial modeling.
• Collaborate with cross-functional teams to enhance investment strategies and operational efficiency within a dynamic and innovative environment.
• Develop and maintain analytical dashboards and data pipelines, ensuring accurate and actionable insights for portfolio management.
• Perform in-depth fund-level and asset-level analytics, including risk-return analysis and market benchmarking.
• Implement financial models to forecast cash flows, assess risks, and optimize portfolio performance.
• Provide insights into macro trends and industry landscapes to inform strategic portfolio decisions.
• Engage in a hybrid work environment, balancing remote and on-site collaboration effectively.
• Take on a role with opportunities for innovation, growth, and entrepreneurial initiative.

Key Responsibilities & Duties

• Conduct detailed portfolio composition analysis, including attribution and contribution analysis for diverse investment types.
• Execute scenario analyses, stress tests, and macro-trend evaluations to inform investment strategies.
• Collaborate with technology teams to develop and maintain data pipelines for analytics dashboards.
• Perform back-testing and forecasting for investment models, including NPV, IRR, and ROE calculations.
• Provide rolling NAV and cash flow projections to support portfolio management decisions.
• Monitor industry trends to enhance macro analytics and market mapping capabilities.
• Collaborate with investor relations teams to deliver analytics that enhance client engagement and transparency.
• Support risk and liquidity reviews by integrating portfolio analytics with financial oversight processes.

Job Requirements

• Bachelor’s degree in Finance, Econometrics, Data Science, or a related field.
• Minimum of 4 years of experience in private markets analytics, portfolio management, or investments.
• Proficiency in financial modeling, data analysis, and accounting principles.
• Expertise in return attribution, risk-adjusted metrics, and J-curve/L-curve analytics.
• Experience with analytical tools such as Excel, Tableau, Python, and Power BI.
• Preferred certifications: CFA, CAIA, FRM, or ACA, or actively pursuing one.
• Strong problem-solving skills and ability to deliver under tight deadlines.
• Knowledge of ETL processes and cloud warehouse technologies like Snowflake and Databricks is advantageous.