Senior Data Analytics Reporting Analyst - Investment Consultancy & Oversight and Multi-Manager Solutions

About the role

The Data Engineering team serves as a core member of the quantitative and data infrastructure supporting the Investment Consultancy & Oversight and Multi-Manager Solutions businesses. This role is responsible for data sourcing, validation, analytical development, and reporting production in direct partnership with the Coverage Analysts and Investment Strategy and Research team as well as the investment professionals within the Multi-Manager Solutions business.

Responsibilities

• Proactively identify opportunities to improve analytical capabilities and bring forward ideas that enhance the efficiency and impact of the team's output.
• Work in close, ongoing collaboration with the Coverage Analysts and Investment Strategy and Research team, as well as the investment professionals within Multi-Manager Solutions, to understand their analytical needs and translate those needs into effective data solutions, models, and reporting.
• Participate in research discussions and project planning to ensure that data and analytical capabilities are aligned with the priorities of both Investment Consultancy & Oversight and Multi-Manager Solutions.
• Proactively identify gaps in existing tools or data coverage and propose solutions that enhance the teams' ability to generate insights and support investment decision-making.
• Source, validate, and maintain investment data across multiple platforms and databases to support all investment oversight, research, and multi-manager activities.
• Ensure data quality, consistency, and accessibility for the Coverage Analysts, Investment Strategy & Research team, Multi-Manager Solutions team, and broader stakeholders.
• Partner with Enterprise Technology and vendor teams to resolve data issues and enhance data infrastructure.
• Manage data feeds and relationships with key data providers including Bloomberg, FactSet, Morningstar, and Aladdin.
• Build, maintain, and enhance quantitative models, analytical tools, and performance attribution systems used across Investment Consultancy & Oversight and Multi-Manager Solutions.
• Develop automated solutions that improve the efficiency and accuracy of recurring analytical workflows.
• Support backtesting, scenario analysis, and factor-based research efforts in coordination with the Investment Strategy & Research team and Multi-Manager Solutions investment professionals.
• Apply sound model governance practices including documentation, version control, and validation protocols.
• Continuously evaluate reporting processes for opportunities to improve clarity, efficiency, and automation.
• Design and maintain dashboard capabilities that provide Coverage Analysts, Investment Strategy and Research Analysts, and Multi-Manager Solutions professionals with ready access to the data and visualizations they need.
• Identify opportunities to leverage emerging capabilities including artificial intelligence and machine learning to enhance the team's analytical infrastructure.
• Support new product development and market research efforts through data analysis and quantitative modeling.
• Approach recurring process with a critical eye toward whether it can be done better, faster, or more reliably.
• Collaborate with Enterprise Technology and IT teams on technology enhancement projects and platform development.
• Support the Investment Risk Management team with data and analytical needs as required.
• Coordinate effectively with team members across Boston, New York, London, and India to ensure seamless collaboration across time zones and consistent quality standards.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, or a related quantitative field.
• Experience in data engineering / analytics, quantitative development, or reporting within institutional investment management or a related financial services environment.
• Advanced proficiency in programming languages (Python, R, SQL) and experience with database management platforms.
• Ability to communicate complex and technical concepts clearly and concisely to both technical and non-technical audiences, in written and verbal form.
• Strong organizational and project management skills, with a demonstrated ability to manage competing priorities and deliver high-quality work on deadline.

Preferred Qualifications

• CFA, CAIA, FRM, or similar professional certification.
• Strong understanding of investment data, portfolio analytics, performance attribution, and risk measurement, with the ability to contextualize quantitative output within a broader investment framework.
• Experience with financial data providers and platforms such as Bloomberg, FactSet, Morningstar, eVestment, and Aladdin.