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, leveraging AI tools for automated anomaly flagging and pattern detection. Own daily production oversight and manage incidents end-to-end, from triage and root cause analysis to post-incident documentation and runbook maintenance. Build SQL scripts and Python notebooks to automate recurring QA tasks, reduce manual effort, and improve consistency while partnering with Model Engineering and Research on complex data discrepancies. Oversee timely distribution of model data to internal and external clients, coordinate delivery milestones, and serve as the operational point of contact for global client queries. Proactively identify workflow inefficiencies to drive automation, process re-engineering, and smarter ways of working within the 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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