Real Assets Data Operations and Research Specialist

MSCI Services

You will be working as part of a growing team of real estate performance analysts who provide real estate direct property indexes, benchmarks, performance analysis reports, and custom/bespoke analysis to global real estate asset managers and asset owners.

Key Responsibilities:

Data Quality Assurance

• Implement and oversee

  data quality controls

  for real estate data, including validation, cleansing, and verification processes.
• Perform regular

  audits of data

  to ensure accuracy and compliance with internal and external standards.
• Develop and maintain

  data quality metrics and KPIs

  to track and improve data quality over time.

Data Management & Improvement

• Collaborate with cross-functional teams to understand

  data needs and requirements

  .
• Identify and address data quality issues and root causes by designing and implementing solutions that improve

  data reliability

  .
• Coordinate with data providers and vendors to ensure timely and accurate delivery of real estate data.

Reporting & Analytics

• Generate periodic reports on

  data quality performance, trends, and improvement areas

  for senior management.
• Support data-driven decisions by providing accurate data and insights to stakeholders across the organization.
• Assist in the development of

  dashboards and visualization tools

  for real-time monitoring of data quality metrics.

Process Optimization & Automation

• Identify opportunities to

  streamline and automate data quality processes

  , reducing manual intervention and enhancing efficiency.
• Participate in system upgrades, data migrations, and other initiatives, ensuring

  data integrity and smooth transitions

  .

Compliance & Governance

• Ensure adherence to

  data governance policies and industry regulations

  for real estate data.
• Assist in the development and implementation of data governance frameworks, standards, and best practices.
• Train team members and other stakeholders on data quality policies and protocols.

Qualifications:

• Proficiency in

  data quality tools and software (e.g., SQL, Python, R)

  .
• Familiarity with

  data visualization tools (e.g., Tableau, Power BI)

  .
• Strong

  analytical, problem-solving, and attention-to-detail skills

  .
• Ability to communicate complex data concepts to non-technical stakeholders effectively.
• Collaborative team player with a proactive approach to improving data quality processes.