Risk Model Analytics Operations - Senior Associate

MSCI Inc.; Philippines; On-site; PHP 1,200,000 - 2,400,000; Full time

Benefits offered by this job

Global exposure

Flexible work

Learning opportunities

Inclusive culture

Job summary

MSCI invites a Senior Associate for Risk Model Analytics Operations to own the production lifecycle of multi-asset class factor models and risk data. You will supervise QA, data validation, incident management, and client delivery while pushing automation and AI-driven improvements across global teams.

You’ll collaborate with Research, Model Engineering, and Data teams to ensure timely, accurate model outputs, scalable runbooks, and SLA-adherent distribution across channels.

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.

Responsibilities

• Own and execute structured QA checks on model outputs and data pipelines — understand root causes and data behavior.
• Drive QA enhancements including anomaly detection, reduction of false positives, and relevant QA rules for signal quality.
• Build SQL scripts and Python notebooks to automate recurring QA tasks and improve consistency.
• Investigate data discrepancies with Model Engineering and Research, engaging on complex model and data issues.
• Leverage AI tools to enhance QA workflows — automated anomaly flagging and agentic workflows via MCP tooling.
• Own daily production oversight for multi-asset class models — ensure runs complete accurately and issues are caught before impacting clients.
• Manage incidents end-to-end — triage, root cause analysis, stakeholder communication, post-incident docs.
• Maintain and improve runbooks, escalation procedures, and SOPs to reduce time-to-resolution and prevent recurrence.
• Oversee timely distribution of factor model data to internal/external clients across channels.
• Coordinate client delivery milestones, manage exceptions, and ensure SLA adherence for model packages.
• Serve as operational contact for client delivery queries across global counterparts.
• Identify and eliminate inefficiencies in production workflows — drive automation and smarter workflows.
• Champion AI/tooling adoption within the team — evaluate and manage AI tools and MCP integration.
• Build and maintain metrics dashboards surface actionable insights; define data to capture and why.
• Drive knowledge transfer, cross-training, and documentation for operational resilience.

Skills

Python

SQL

QA

Incident mgmt

Automation

AI tools

Communication Eng

Operational excellence

Education

Bachelor's in quantitative field

Tools

Snowflake

LangChain

MCP

ServiceNow

Jira

Job description

Your Team 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

Minimum Qualifications

Your skills and experience that will help you excel

• 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

About MSCI

What we offer you

• Transparent compensation schemes and comprehensive employee benefits, tailored to your location, ensuring your financial security, health, and overall wellbeing.
• Flexible working arrangements, advanced technology, and collaborative workspaces.
• A culture of high performance and innovation where we experiment with new ideas and take responsibility for achieving results.
• A global network of talented colleagues, who inspire, support, and share their expertise to innovate and deliver for our clients.
• Global Orientation program to kickstart your journey, followed by access to our Learning@MSCI platform, AI Learning Center , LinkedIn Learning Pro and tailored learning opportunities for ongoing skills development.
• Multi-directional career paths that offer professional growth and development through new challenges, internal mobility and expanded roles.
• We actively nurture an environment that builds a sense of inclusion belonging and connection, including eight Employee Resource Groups. All Abilities, Asian Support Network, Black Leadership Network, Climate Action Network, Hola! MSCI, Pride & Allies, Women in Tech, and Women’s Leadership Forum.

At MSCI we are passionate about what we do, and we are inspired by our vision – to power better decisions. You’ll be part of an industry-leading network of creative, curious, and entrepreneurial pioneers. This is a space where you can challenge yourself, set new standards and perform beyond expectations for yourself, our clients, and our industry.

MSCI strengthens global markets by connecting participants across the financial ecosystem with a common language. Our research-based data, analytics and indexes, supported by advanced technology, set standards for global investors and help our clients understand risks and opportunities so they can make better decisions and unlock innovation. We serve asset managers and owners, private-market sponsors and investors, hedge funds, wealth managers, banks, insurers and corporates.

MSCI Inc. is an equal opportunity employer. It is the policy of the firm to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, creed, age, sex, gender, gender identity, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, pregnancy (including unlawful discrimination on the basis of a legally protected parental leave), veteran status, or any other characteristic protected by law. MSCI is also committed to working with and providing reasonable accommodations to individuals with disabilities. If you are an individual with a disability and would like to request a reasonable accommodation for any part of the application process, please email [e-mail] and indicate the specifics of the assistance needed. Please note, this e-mail is intended only for individuals who are requesting a reasonable workplace accommodation; it is not intended for other inquiries.