Investment Analyst - Global Real Estate

UBS•Dallas, TX

1d•Onsite

About The Position

We’re looking for an Investment Analytics Analyst to gather, integrate, organize, validate, reconcile and transform internal operational and financial data, external benchmark data from sources such as the National Council of Real Estate Investment Fiduciaries (NCREIF) and MSCI, and inputs from multiple systems and service providers. This role involves producing recurring reports, scorecards, interactive Power BI dashboards and presentation materials that show returns, attribution, expenses, income drivers, key performance indicators (KPIs) and performance trends. The analyst will prepare benchmark, scorecard, operational and portfolio analysis, complete ad hoc analysis and data requests, and maintain investment performance records, databases, reporting files and supporting datasets. The position requires using Excel, Python, Power BI, Data Analysis Expressions (DAX) and SQL to build and maintain data frameworks, reusable scripts, queries, data models and dashboard components. Additionally, the role involves using AI-assisted tools responsibly to explore data, develop code, summarize trends, validate logic, detect anomalies, create documentation and generate insights, while collaborating with Fund Operations, Portfolio Management and Accounting to strengthen controls and improve consistency. The analyst will also be responsible for improving the investment analytics data model and streamlining workflows by identifying and implementing process improvements.

Requirements

3–5 years of experience in investment analytics, performance measurement, reporting, quantitative analysis, data analytics, or a related technical analytics role within real estate, private equity, asset management, or a related field.
Experience supporting investment performance reporting and a solid understanding of common metrics across asset-, investment-, or fund-level analyses.
Strong technical proficiency in advanced Excel, Python, SQL, Power BI, and DAX, including experience building automated reporting tools, data models, dashboards, or repeatable analytical workflows.
Demonstrated interest in and practical use of AI-enabled tools to improve analytical productivity, automate routine tasks, support code development, summarize insights, or enhance reporting workflows.
Strong written and verbal communication skills, with the ability to summarize analyses clearly and work effectively with both technical and non-technical stakeholders.
Strong attention to detail, sound judgment, and the ability to manage multiple priorities and deadlines in a fast-paced environment.
Analytical and detail-oriented mindset with a strong commitment to accuracy, quality, data integrity, and continuous improvement.
Technically curious and proactive, with the ability to learn new tools, evaluate emerging technologies, and apply AI and automation thoughtfully to improve business outcomes.
Collaborative team player who works effectively across functions and builds strong working relationships with internal stakeholders.
Ability to take ownership of assignments, exercise initiative, and contribute to projects with appropriate guidance from senior team members
Curious to explore how AI can improve how we build, deliver, and optimize workflows. You do this with sound judgment – validating outputs and aligning with policies, risk standards, and ethical use

Nice To Haves

Familiarity with industry benchmarks such as NCREIF and MSCI preferred.

Responsibilities

Gather, integrate, organize, validate, reconcile and transform internal operational and financial data, external benchmark data from sources such as the National Council of Real Estate Investment Fiduciaries (NCREIF) and MSCI, and inputs from multiple systems and service providers, maintaining supporting documentation so data is accurate, consistent and ready for recurring analysis and reporting
Produce recurring reports, scorecards, interactive Power BI dashboards and presentation materials that show returns, attribution, expenses, income drivers, key performance indicators (KPIs) and performance trends at asset, investment and fund level for investment committee meetings, portfolio reviews and other internal reporting
Prepare benchmark, scorecard, operational and portfolio analysis for review, highlighting material variances and trends against internal targets and relevant market indices to help business units monitor investment performance and support investment decisions and ongoing portfolio monitoring
Complete ad hoc analysis and data requests, draft clear analytical narratives and develop portfolio review materials that make reliable insights easier for stakeholders to access, understand and act on
Maintain investment performance records, databases, reporting files and supporting datasets, and calculate measures such as internal rate of return (IRR), time-weighted returns and equity multiples at fund or asset level to support analytics, benchmarking and track-record reporting
Use Excel, Python, Power BI, Data Analysis Expressions (DAX) and SQL to build and maintain data frameworks, reusable scripts, queries, data models and dashboard components that automate data collection, validation, transformation and investment performance reporting
Use AI-assisted tools responsibly to explore data, develop code, summarize trends, validate logic, detect anomalies, create documentation and generate insights while protecting confidential information, applying appropriate human review and data governance, and verifying outputs
Collaborate with Fund Operations, Portfolio Management and Accounting to gather and validate inputs used in performance reporting and analysis, strengthen controls and improve consistency across recurring analytics and reporting
Improve the investment analytics data model and streamline workflows by identifying and implementing process improvements that reduce manual effort, make recurring data collection, validation, reconciliation and reporting more efficient, and document technical processes, data lineage, assumptions and AI-assisted workflows to support transparency, repeatability and continuity