Manager - Investment Performance Analysis

State Street.
Bangalore, India
Not disclosed
17 Jan 2022
24 Jan 2022
Contract type
Full time
Experience level

Key responsibilities:

  • The candidate will be part of Performance & Attribution services within IMS Investment Analytics.
  • The role involves working on a new project involving performance data migration from legacy platform to a new engine and setting up daily activities.
  • Able to build/amend VBA codes and run complex SQL queries.
  • Attending daily calls with the onshore team and providing project status update.
  • Interacting with upstream teams to address data flow issues affecting the performance team.
  • Should be able to handle large databases (MS Access) and design and implement the automation of manual processes.
  • Ensure coding, testing, and documentation tasks are successfully performed for new application development as well as enhancements to existing system functionalities.
  • Provide necessary support to other Investment Analytics functions like GIPS Services, Change Management, and JV Oversight.

Supportive responsibilities:

  • Able to develop code, which is clear, concise, and technically correct.
  • Should be able to work on complex change management requests and complete the logs
  • on or before the stipulated time frame.
  • Should be able to resolve critical client queries on application and reporting.
  • Prepare standard operating procedure for new transitions/tasks.


Education & Experience:

  • Bachelors/Masters in Accounting/Finance.
  • 7 to 10 years experience in Fund performance measurement/Attribution.
  • Pursuing CFA/FRM/CIPM would be an added advantage.


  • Should have previously worked on new transitions/data migration.
  • Should have strong knowledge of VBA/SQL and database development.
  • Able to develop complex VBA/SQL queries using various joins and develop dynamic codes (Subqueries and Join conditions, correlated subqueries, Database creation, Tables, and indexes creation) for optimum performance over large datasets.

For further information, and to apply, please visit our website via the “Apply” button below.

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