Lead - Data Operations - Automation & Transitions
MSCI · Coimbatore
The MSCI Sustainability & Climate Data Collection team acquires sustainability and climate
data at scale, quality-assures what it collects, and maintains high data quality across every dataset
feeding MSCI's ESG products. This role delivers initiatives within the S&C transformation agenda,
centred on large-scale collection and taking ownership of the collection transformation project with
the team and internal stakeholders.
- Drive insightful research
Source, analyse and process global company disclosures using generative AI. - Unlock the power of information
Work across annual reports, websites, quantitative feeds, crawlers and news to create actionable
intelligence. - Rethink data collection with AI
Design AI-assisted, scalable models for multi-channel sourcing and full issuer coverage. - Automate and scale methodologies
Build collection methods that turn unstructured data into structured insight through AI-driven
\"electronification\". - Build next-generation extraction models
Build and refine generative AI extraction models for accuracy, efficiency and performance. - Lead and optimise AI agents
Guide AI agents and act as the validation layer, sharpening output through expert feedback. - Shape the future of data operations
Partner with technology and transformation teams to design and engineer data workflows. - Improve quality and efficiency
Strengthen data quality diagnostics, reduce manual intervention and raise operational efficiency. - Collaborate for impact
Define data needs and quality control frameworks with internal and downstream teams. - Engage with companies and clients
Process company feedback, answer client queries and support a transparent, data-driven ecosystem.
- Bachelor's degree in Finance, Economics, Business, Engineering, Science, Environmental Science, Data Science or a related field.
- 7–12 years in large-scale data collection, research, data operations or supply-chain analysis. Climate or sustainability a plus
- A track record of leading projects to completion with stakeholders and team members.
- At least 4 years of people management experience, evidenced on paper. Required
- Applying GenAI and LLMs to extraction, summarisation, classification or workflow automation, including prompt-based workflows and model evaluation.
- Familiarity with AI agents, retrieval-augmented generation (RAG) or ML-assisted quality. Required
- Hands-on Python for automation, web scraping, API integration, data cleaning and high-volume processing.
- Working knowledge of SQL and comfort with large datasets.
- A strong analytical mindset for interpreting complex corporate disclosures and drawing out supply-chain insights.
- Excellent written and verbal communication in English.
- Effective collaboration with global teams across time zones and cross-functional partners.