Risk Model Analytics Operations - Senior Associate
On-siteDasmarinas, National Capital Region, Republic of the Philippines
Job Summary
Execute structured QA checks on multi-asset class factor model outputs and data pipelines, building SQL scripts and Python notebooks to automate recurring tasks and reduce false positives. Manage end-to-end incident resolution including triage, root cause analysis, and stakeholder communication while maintaining operational runbooks and SOPs. Oversee timely distribution of model data to internal and external clients, ensuring SLA adherence and serving as the operational point of contact for delivery queries. Proactively identify workflow inefficiencies to drive automation, process re-engineering, and AI tool adoption via MCP and agentic workflows. Build metrics dashboards to surface actionable operational insights and lead cross-functional knowledge transfer efforts within the global Production Shared Services team.
Required 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
Desired 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
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