Risk Model Analytics Operations - Senior Associate

Responsibilities MSCI's Analytics Factor Model team, part of the broader Production Shared Services (PSS) organization, is seeking a Senior Associate for Risk Model Analytics Operations. The team owns the daily production lifecycle of MSCI's multi-asset class (Equity, Fixed Income, etc) factor models and risk data — ensuring model outputs are accurate, timely, and operationally sound across monitoring, incident management, model distribution, and client delivery. This is a role for someone who doesn't just keep the factory running — you'll be constantly asking how to run it better, faster, and smarter through AI, automation, and process optimization. You will collaborate closely with Research, Model Engineering, and Data teams across global offices. Your Key Responsibilities QA & Data Validation Own and execute structured QA checks on model outputs and data pipelines — going beyond surface-level checks to understand root causes and data behavior Drive QA enhancements including anomaly detection, reduction of false positives, and identification of relevant QA rules that improve overall signal quality Build SQL scripts and Python notebooks to automate recurring QA tasks, reduce manual effort, and improve consistency Partner with Model Engineering and Research to deeply investigate data discrepancies — able to engage technically on complex model and data issues, not just route them Leverage AI tools to enhance QA workflows — including automated anomaly flagging, pattern detection, and agentic AI workflows via MCP tooling Daily Operations & Incident Management Own daily production oversight for multi-asset class factor models — ensuring runs complete accurately and issues are caught before impacting downstream clients Manage incidents end-to-end — triage, root cause analysis, stakeholder communication, and post-incident documentation Maintain and improve runbooks, escalation procedures, and operational SOPs to reduce time-to-resolution and prevent recurrence Model Distribution & Client Delivery Oversee timely and accurate distribution of factor model data to internal and external clients across multiple delivery channels Coordinate client delivery milestones, manage exceptions, and ensure SLA adherence for custom and standard model packages Serve as an operational point of contact for client delivery queries, working cross-functionally with global counterparts Continuous Improvement Proactively identify and eliminate inefficiencies in production workflows — driving automation, process re-engineering, and smarter ways of working rather than accepting the status quo Champion AI and tooling adoption within the team — evaluating, implementing, and managing AI tools, MCPs, and agentic workflows that expand operational capability Build and maintain metrics dashboards that surface actionable operational insights — defining what data the team should be capturing and why Drive knowledge transfer, cross-training, and documentation efforts — ensuring operational resilience and reducing single points of failure across the team Your skills and experience that will help you excel Minimum Qualifications Bachelor's degree in Finance, Economics, Mathematics, Statistics, Computer Science, Engineering, or a related quantitative field Minimum 7 years of relevant experience in data operations, production support, or a data-intensive financial services role Demonstrated experience in operational transformation — proactively identifying inefficiencies, optimizing workflows, and driving automation and AI adoption rather than simply maintaining the status quo Strong proficiency in Python and SQL for data analysis, investigation, and workflow automation Demonstrated ability to manage and resolve production incidents end-to-end — from triage to root cause and resolution Solid understanding of data pipelines, model distribution workflows, and operational quality standards Demonstrated ability to use AI tools to enhance