Risk Model Analytics Operations - Senior Associate

MSCI Inc; Philippines; On-site; PHP 900,000 - 1,200,000; Full time

Job summary

MSCI Inc in Philippines seeks Senior Associate for Risk Model Analytics Operations to own daily production of multi-asset factor models and risk data, ensuring accuracy and timely delivery across monitoring, incidents, model distribution and client delivery.

You will drive QA enhancements, automate tasks with Python/SQL, push for AI-driven improvements, and collaborate with Research, Model Engineering, and Data teams worldwide.

Qualifications

• Bachelor's degree in a quantitative field or related discipline.
• 7+ years of experience in data operations, production support, or data-intensive roles.
• Experience transforming operations, automating workflows, and adopting AI—beyond routine maintenance.
• Strong Python and SQL skills for data analysis, investigation, and automation.
• Experience managing production incidents end-to-end, from triage to resolution.
• Understanding of data pipelines, model distribution workflows, and quality standards.
• Experience using AI tools to enhance operational and analytical work.
• Clear written and spoken English communication; able to work with global teams.

Responsibilities

• Own QA checks on model outputs and data pipelines, identify root causes, and ensure data quality.
• Drive QA enhancements, anomaly detection, and reduction of false positives.
• Build SQL scripts and Python notebooks to automate recurring QA tasks.
• Investigate data discrepancies with Model Engineering and Research.
• Oversee daily production for multi-asset class factor models and ensure timely issue resolution.

Skills

Python

SQL

Data analysis

Incident management

QA automation

AI tooling

English communication

Cross-functional collaboration

Education

Bachelor's degree in Finance, Economics, Mathematics, Statistics, Computer Science, Engineering, or related field

Tools

Snowflake

Cloud data platforms

Job description

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.

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

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 operational and analytical work
• Strong written and verbal communication skills in English — able to communicate clearly with both technical teams and client‑facing stakeholders
• Ability to manage multiple priorities under time pressure in a globally distributed team environment

Preferred Qualifications

• Exposure to capital markets, risk analytics & models, or other financial data products
• Experience with cloud data platforms such as Snowflake or equivalent
• Familiarity with AI/LLM-based tools applied to operational workflows — such as automated anomaly flagging, triage, or insight generation
• Experience with agentic AI frameworks such as LangChain, LlamaIndex, or Model Context Protocol (MCP) integration
• Familiarity with Agile/SAFe delivery frameworks — sprints, PI Planning, Jira
• Experience with ServiceNow or equivalent incident and case management platforms
• Master's degree in a quantitative or technical field is a plus