MSCI is a leading provider of investment decision support tools to clients worldwide, ranging from large pension plans to boutique hedge funds. We offer a range of products and services - including indexes, portfolio risk and performance analytics  

Geospatial Data Team is responsible for data quality and maintaining best practices of data management for Climate and ESG data. Cultivating data management best practices and processes that improve the speed and accuracy of data delivery, including data access, quality control, automation, integration and helping setup online data operations. 

• Geospatial Data Acquisition: Gatekeeper for all geospatial data acquisition, ensuring compliance with best practices and drive system development and process set-up to meet “Data Factory” requirements. 

• Data Onboarding & Integration: Oversee the ingestion and integration of third-party data into MSCI systems. Collaborate with product and research teams to prioritize data acquisition efforts. 

• Data Governance Best Practices: Establish and enforce data governance standards for SLA management, new data acquisitions, source changes, and data cataloguing. 

• Process Transformation: Optimize and scale existing data operations by implementing next-generation data acquisition workflows, leveraging cloud-native solutions for improved efficiency and quality. 

• Data Solutions for Research & Product Teams: Partner with research and product teams to develop new methodologies, assess feasibility, and provide practical recommendations on data-driven initiatives. 

• Operations Process Automation: Drive automation of manual processes through hands-on tactical solutions while implementing scalable, long-term production systems. 

• Data QA Engineering: Develop and enhance quality assurance (QA) frameworks for new and existing data. Build efficient QA pipelines, multi-vendor validation systems, and data certification processes. Document findings and share insights with relevant research and product committees 

The Operations Analyst will play a pivotal role in advancing data quality, automation, and operational analytics across Climate geospatial datasets. This role requires strong analytical aptitude, familiarity with data acquisition workflows, and a proactive mindset to scale Data Factory-style operations. The Analyst will help identify system-level bottlenecks, improve data integrity, and drive operational efficiencies through actionable insights and automation initiatives. 

• Unlock the Power of Information: Extract and transform information from diverse sources, including company reports, websites, structured feeds, crawlers, and news articles, into actionable Sustainability and Climate intelligence. 

• Data Operations Analytics: Collaborate with a diverse team of analysts to solve complex data challenges across sourcing, processing, loading, and analysis. Leverage data patterns to detect anomalies and improve pipeline health. 

• Operational Reporting & Documentation: Design and document AI-friendly data collection methodologies that support automation and enable electronification—the transformation of unstructured content into structured, machine-readable insights. Develop SOPs, process flows, incident logs, and dashboards to ensure operational transparency, audit-readiness, and scalable knowledge transfer. 

• Quality Control Optimization & Efficiency: Collaborate with QA engineers and content specialists to design contextual QA checks and multi-layer validation frameworks that enhance diagnostic accuracy. Leverage historical data patterns to refine detection logic, reduce false positives, minimize manual intervention, and increase overall throughput across QA systems. 

• Client Query Management & Communication:  Work closely with Client Coverage teams to resolve issues, respond to inquiries, and ensure clear, timely, and professional communication aligned with MSCI standards.  

• Collaborate for Impact: Partner with internal stakeholders - Research, Technology, and downstream teams—to align on data requirements, define QC scope, and ensure seamless data delivery.  

• Strong attention to detail with a structured, analytical mindset 

• Demonstrated experience with data analysis tools (Excel, SQL, Python, QGIS, GEE ) 

• Commitment to quality control and data management best practices 

• Excellent communication and presentation skills; ability to convey insights to both technical and non-technical audiences 

• Prior experience working in cross-functional, global teams across time zones and geographies 

• Exposure to ESG, Climate, or Geospatial datasets is a plus 

• Experience in issuer communication and operational client engagement 

• Comfortable working in a team across hierarchies, cultures, and functions 

• A proactive, solution-focused work ethic with the ability to manage competing priorities in a deadline-driven environment