Private Markets Data Operations Associate

15 MS Investment Mgmt., Inc.; New York (NY); On-site; USD 90,000 - 135,000; Full time

Job summary

Morgan Stanley Investment Management (MSIM) seeks an Associate, Data Operations — Private Markets to support data operating model execution across the Private Markets platform. The role involves data quality controls, reconciliations, and governance with internal teams and external providers.

You will help ensure completeness, accuracy and traceability of critical data, investigate exceptions, and contribute to process improvements while supporting modernization of the data platform.

Qualifications

• 3–6 years of experience in investment management, fund operations or data operations.
• Strong analytical and problem-solving skills with ability to investigate data exceptions.
• Understanding of Private Markets data such as capital activity, positions, cash, P&L and NAV data.
• Familiarity with data governance concepts, lineage, CDEs and data-quality rules.
• Advanced Excel skills; SQL knowledge is beneficial.

Responsibilities

• Execute data quality and control processes for Private Markets data across sources.
• Investigate and resolve data exceptions with root-cause analysis.
• Perform reconciliations and variance analysis on investment and fund data.
• Support data governance activities including maintenance of CDEs and data definitions.
• Produce data-quality and operational reporting with SLA metrics.
• Collaborate with Operations, Technology and external providers to drive remediation.

Skills

Data Operations

Excel

SQL

Education

Bachelor's degree in Accounting, Finance, Commerce, Business, Information Systems or related

Tools

eFront

Investran

Job description

Morgan Stanley Investment Management (MSIM) seeks an Associate, Data Operations — Private Markets to support data operating model execution across the Private Markets platform. The role involves data quality controls, reconciliations, and governance with internal teams and external providers.

You will help ensure completeness, accuracy and traceability of critical data, investigate exceptions, and contribute to process improvements while supporting modernization of the data platform.