Distinguished Principal Engineer - AI Science

The Principal AI Scientist / Principal AI Engineer at MSCI is a high-impact, individual contributor role that sits at the intersection of advanced data science, machine learning, and product engineering. Operating within the core product teams, this leader directly shapes the algorithms powering the company's multi-billion-dollar financial platform and products at MSCI.

The role focuses on building production-grade machine learning models, scaling AI pipelines, and embedding generative AI agents to solve financial workflows for clients worldwide.

• Algorithm & Model Development
• Advanced ML Application: Apply cutting-edge techniques in Natural Language Processing (NLP), Causal-ML, Deep Learning, Reinforcement Learning, and Generative AI (LLMs) to solve real-world financial problems.
• Experimentation & Prototyping: Partner directly with software engineers, product managers, and designers to design rapid experiments and build Minimum Viable Products (MVPs) to test out 0 1 AI-driven experiences.
• Technical Leadership & Technical Rigor
• Team Stewardship: Lead the technical roadmap for a product area or domain. You will drive end-to-end architecture designs for the team's data science solutions and enforce best practices in code quality, algorithm development, experiences and agentic engineering.
• AI Guardrails & Evaluation: Build and standardize evaluation methodologies to strictly validate model accuracy, explainability (XAI), and fairness, ensuring compliant and responsible AI practices.
• Reusable Pipeline Infrastructure: Architect robust, end-to-end reusable pipelines that smoothly transition algorithmic models from standalone research prototypes directly into stable production-level services.
• Cross-Functional Influence & Mentorship
• Evangelism: Translate complex statistical and algorithmic logic into digestible, business-focused insights for senior leadership and non-technical stakeholders.
• Industry & Academic Connection: Actively track the latest developments in academia and broader tech sectors to proactively integrate emerging AI paradigms into MSCI Products.
• Talent Growth: Provide technical mentorship to junior engineers, fostering a collaborative culture of continuous technical excellence.
• Experience: 10+ years of cumulative industry experience in a dedicated data science or machine learning capacity.
• Leadership Track Record: 3+ years acting as a technical lead, steering data science initiatives or managing delivery of mission-critical ML workflows.
• Deep Math & ML Core: Expert-level proficiency across optimization paradigms (e.g., gradient methods, Bayesian optimization) and foundational ML frameworks.
• Technical Stack: Deep hands-on coding experience in big data environments using general-purpose languages like Python, Scala, Java, or R, alongside strong SQL capabilities.
• Education: Bachelor's, Master's, or Ph.D. in a highly quantitative discipline (such as Computer Science, Statistics, Mathematics, Operations Research, or Economics).