Associate AI Engineering

Your Team Responsibilities MSCI Data AI Engineering is a central team responsible for building and managing a broad suite of data-centric applications and capabilities that support all MSCI business verticals.  A core part of our mission is ensuring data quality, consistency, and reliability across MSCI’s products. The team designs and implements robust AI-driven data quality enhancements to guarantee that downstream analytics, models, and client-facing solutions are built on trusted data. As a senior member of this team, you will work alongside highly motivated professionals, providing technical while helping to challenge and elevate the group to produce best-in-class products and technology Your Key Responsibilities KEY RESPONSIBILITIES Lead the design and development of AI & data science applications, driving MSCI’s ongoing AI adoption journey and setting technical direction for the data quality team. Implement ML/NLP/GenAI/Agentic AI, and advanced anomaly detection methodologies (including statistical, ML-based, and AI-driven approaches) within data science tools to deliver new functionality for both the internal production platform and the client delivery platform. Partner closely with Product Management, Quality Assurance, Data Operations, and IT Infrastructure throughout all stages of the development lifecycle, influencing roadmap priorities and ensuring reliable, high-quality, and scalable solutions. Evaluate and introduce new tools, frameworks, and methodologies to strengthen the team’s AI/ML and data quality capabilities. Your skills and experience that will help you excel SKILLS & EXPERIENCE Bachelor’s or Master’s degree in Computer Science, Mathematics, Engineering, or a related field, with 6+ years of relevant experience in AI/ML engineering. Proven track record of finding patterns in data, building statistical models, and driving data exploration, visualization, and data mining at scale. Demonstrated experience designing, developing, and deploying AI and ML solutions to production, including ownership of architecture and scalability decisions. Strong hands-on experience in Python & NLP Deep expertise in anomaly detection methodologies, including statistical techniques, ML-based approaches, and AI-driven detection systems for identifying irregularities, data drift, and quality issues at scale. Hands-on experience building or deploying LLM-based and Agentic AI solutions in production is a strong plus. Experience mentoring engineers and leading technical initiatives Self-motivated, proactive, with a strong sense of ownership and drive toward delivery. Experience with cloud-based solutions, especially Azure or Google Cloud Platform (GCP), including deploying and scaling ML workloads in production. Knowledge of DevOps practices and tools for continuous integration and deployment. About MSCI What we offer you Transparent compensation schemes and comprehensive employee…