We are seeking a Production Support Expert with strong expertise in SAS Risk Management Systems to ensure the stability, availability, and performance of mission-critical risk and regulatory applications. The candidate will be responsible for resolving incidents, monitoring batch jobs, supporting business users, and working closely with IT and risk teams to meet operational SLAs.
Key Responsibilities:
- Provide L2/L3 production support for SAS Risk Management solutions, including batch processing and report generation
- Monitor and troubleshoot SAS Grid jobs, ETL pipelines, and database interactions
- Diagnose and resolve issues related to data ingestion, model execution, and regulatory report generation
- Analyze and interpret SAS logs, Grid logs, and database logs to identify root causes of failures
- Support regulatory reporting processes such as Basel III/IV, IFRS 9, CECL, ICAAP, etc.
- Assist in code deployments, patching, and environment migrations (DEV/TEST/PROD)
- Maintain system health and job schedules using Control-M, Autosys, or cron
- Collaborate with risk modelers, compliance teams, and IT infrastructure to resolve production issues
- Create and maintain documentation including runbooks, SOPs, RCA reports, and support guides
- Ensure adherence to ITIL processes for incident, change, and problem management
Requirements
Required Skills & Qualifications:
Technical:
- 5+ years experience with SAS tools: Base SAS, SAS Grid, SAS EG, SAS DI Studio
- Strong Unix/Linux skills and experience with shell scripting (bash/ksh)
- Proficient in SQL and Oracle or similar RDBMS
- Experience with job schedulers like Control-M, Autosys, or UC4
- Familiarity with risk data models (PD, LGD, EAD, RWA) and regulatory reporting requirements
- Ability to read and debug SAS logs and troubleshoot data/model issues
Functional:
- Experience supporting SAS solutions for credit, market, or operational risk
- Understanding of regulatory compliance frameworks (Basel II/III/IV, IFRS 9, CECL, etc.)
- Knowledge of model lifecycle management and production validation processes