Role overview
Your Team Responsibilities:
Our team is responsible for building and scaling enterprise-grade AI platforms that transform how MSCI delivers analytics, insights, and client servicing workflows across multiple verticals including Analytics, Sustainability & Climate, Ratings, and Governance. We architect intelligent automation systems, AI agents, pre-screening platforms, and client-query solutions that significantly improve productivity, reduce operational overhead, and enhance data quality across the organization.
As a core part of this transformation, the team develops multi-tenant AI-driven applications, integrates AI into critical decision workflows, and ensures our systems meet rigorous standards for accuracy, regulatory compliance, security, and scalability. The team also leads modernization efforts across cloud infrastructure (GCP/Azure), NLP pipelines, data services, and AI-efficiency initiatives that support MSCI’s long-term AI strategy.
This role offers the unique opportunity to work on diverse, high-impact AI applications that shape how the world's largest financial institutions understand and navigate complex market dynamics.
Your Key Ressponsibilities:
- Design and implement enterprise-scale AI architectures for processing and analyzing complex, multi-dimensional financial and alternative data
- Architect end-to-end AI/ML pipelines that handle multi-modal data sources including structured market data, unstructured documents, and real-time feeds
- Apply cutting-edge AI techniques (including LLMs) to solve MSCI's diverse AI use cases
- Implement MLOps best practices and automated systems for model deployment, monitoring, and continuous improvement across multiple product lines
- Collaborate with product teams and domain experts to translate complex requirements into scalable technical solutions
- Provide technical guidance and mentorship to other engineers on AI/ML best practices and architectural decisions
- Partner with MSCI Research teams to advance the state of AI applications in financial analytics
- Drive technical excellence through code reviews, design documentation, and knowledge sharing across the organization
- Help improve AI Engg team's productivty by using AI agents to automate tasks
Your skills and experience that will help you excel:
- 6+ years of experience designing, building, and deploying AI/ML systems at enterprise scale.
- Expert-level proficiency in modern AI/ML frameworks (TensorFlow, PyTorch) and distributed computing platforms (Spark, Ray, Flink, Beam).
- Proven experience architecting and delivering large-scale, production-grade AI platforms handling complex and high-volume data.
- Advanced knowledge of NLP, computer vision, and time-series analysis, with hands-on application in real-world use cases.
- Experience working with financial data, risk modeling, or quantitative analytics (highly desirable).
- Strong background in system design and integration, including:
- MCP workflows
- DB/API orchestration
- Web frameworks
- Multi-tenant data pipelines
- Expertise in cloud engineering across GCP and Azure, including:
- Cloud architecture
- Security compliance
- Disaster Recovery (DR)
- Kubernetes & serverless pipelines
- IaC using Terraform
- Solid understanding of MLOps practices, including model versioning, monitoring, A/B testing, CI/CD automation, and retraining pipelines.
- Excellent technical communication skills, with the ability to articulate complex AI concepts to varied stakeholders.
- Demonstrated cross-functional collaboration with engineering, research, analytics, product, and governance teams.
- Prior experience publishing research or speaking at AI/ML conferences is a strong plus.
- Strong passion for solving complex analytical challenges with AI-driven solutions in financial markets.
- Demonstrated commitment to AI innovation, including refinement of agentic frameworks, prompt engineering, and platform enhancements to improve product quality and efficiency.
About MSCI:
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