Analyst - Real Estate Finance Data Management & Analytics
Role Overview
This Analyst Wipro role supports world’s largest alternative investment management company within the Real Estate Finance, working closely with global business, product and functional teams across the US, Europe and APAC. The role offers exposure to real estate equity and debt, open- and closed-ended vehicles, and a range of asset classes shaped by client’s thematic investment approach. It combines financial judgement, business acumen and data skills to improve the processes and insights behind valuations, performance, planning and reporting, while building foundations for automation and frontier AI deployment.
Key Responsibilities
• Tackle complex finance and data challenges alongside client’s Real Estate Finance teams, using financial analysis and data to generate insights and develop solutions across the global platform
• Analyse valuations, investment performance, financial statements and forecasts to understand underlying drivers, investigate discrepancies and support management and investor reporting.
• Translate financial questions into analysis and data requirements, connecting fund- and investment-level data to actionable insights.
• Build to trusted financial-data foundations through consistent definitions, reconciliations, controls and traceability across funds, products and functions.
• Improve existing finance processes through hands-on analysis, data and automation, reducing manual work and improving scalability and control.
• Apply industry-leading AI tools and frontier models to finance use cases, enhancing analytics and automating workflows with appropriate financial validation.
• Take solutions from initial analysis and requirements through testing and implementation, working across Wipro, client’s Finance, Technology, Innovations and Transformation teams.
Experience & Capabilities
• 1-3 years of experience, with strong analytical capabilities and demonstrated experience solving financial or data-driven problems.
• Bachelor’s or master’s degree from a Tier-1 college or university in Finance, Accounting, Engineering or Information Systems; CA, CPA, CFA or an equivalent qualification is an advantage.
• Experience in investment banking, asset management, private markets, fintech, finance transformation or another fast-paced, data-intensive financial environment.
• Experience applying industry-leading AI tools or frontier models to analytics and workflow automation is an advantage; exposure to Copilot, Cowork or Copilot Studio is also an advantage.
• Strong analytical and financial-statement skills, with the ability to understand financial drivers, investigate variances and connect detailed analysis to business questions and decisions.
• Experience in fund finance, including capital calls, distributions, liquidity, net income, fees and expenses, valuations, mark-to-market analysis and GAV-to-NAV reconciliations, is an advantage.
• Experience in investment performance analysis, including IRR, time-weighted returns, money multiples, attribution and benchmarking, is an advantage.
• Experience in FP&A, including budgeting, forecasting, variance analysis, financial modelling and scenario analysis, is an advantage.
• Exposure to real estate equity or debt, including loan operations, leverage, hedging and currency exposure, is an advantage.
• Ability to work effectively with business and technology teams, communicate analysis clearly and translate financial questions into data requirements and actionable insights.
• Hands-on experience analysing and modelling complex financial datasets, with an understanding of data structures, quality, lineage and trusted datasets.
• Experience with analytical, automation or visualisation tools such as Alteryx, Tableau, Power BI or Sigma is an advantage.
• Demonstrated interest in improving finance processes through data, analytics and automation, with the ability to contribute from analysis and requirements through testing and implementation.
Source: the employer's careers page. Last checked 2026-10-25. Posted 2026-10-10.
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