Data Operations - Private Markets, Associate, Investment Management
Morgan Stanley (company site, opens in a new tab)3–6 yrsMumbaiOn-siteDirect career pageEst. 12–22 LPA
Posted 14h ago
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Job description
Structured overview of role & requirements
About This Role
- Oversee and control data quality from external fund administrators and internal platforms for Private Markets, ensuring data completeness, accuracy, timeliness, and fitness for use.
- Investigate and resolve data exceptions including root cause analysis and escalation, supporting governance and executing data-quality controls and reconciliations for key investment and operational data.
- Collaborate with Operations, Technology, Data Governance, and external partners to maintain data governance standards, generate data-quality reports, and drive continuous improvements and automation initiatives.
Minimum Requirements
- 3–6 years of experience in investment management, fund administration, financial services or similar complex data environment, with exposure to Data Operations or Fund Accounting.
- Working knowledge of Private Markets products and operating processes (private equity, private credit, real estate, infrastructure, or alternative investments).
- Proficiency in advanced Excel; familiarity with SQL or equivalent data query/analysis tools is beneficial.
- Bachelor’s degree in Accounting, Finance, Commerce, Business, Information Systems or related field; professional qualifications (CA, CPA) or progression towards such is beneficial.
Ideal Candidate Profile
- Experienced in Private Markets fund data including capital activity, positions, cash, P&L, NAV, and fees, with ability to reconcile and investigate data from multiple sources.
- Disciplined with a strong control mindset and attention to detail, able to maintain clear documentation and audit trails while understanding business process implications of data.
- Able to work cross-functionally and communicate complex data issues effectively across global teams and external service providers, supporting governance and continuous improvement of data operations.