Supports corporate credit ratings through financial modeling, data reconciliation, credit-document review, industry research, monitoring material events, and preparation of analytical reports. Maintains operational databases and company and peer-group financial metrics, researches filings and industry publications, and collaborates with global analysts. Ensures compliance with regulatory and company policies while managing multiple tasks accurately and contributing effectively to the team.

Designs and maintains automated data quality frameworks, validation controls, anomaly monitoring, and source-to-target reconciliation processes for large-scale financial datasets. The role validates data from market-data providers, embeds quality controls into ETL/ELT pipelines, supports new dataset onboarding, and performs profiling and root-cause analysis. Requires advanced Python, SQL, and PySpark skills, financial data expertise, and exposure to AWS-based platforms and AI productivity tools.

Develops investment analytics, portfolio monitoring, performance measurement, risk reporting, benchmark analytics, and financial data dashboards. Builds scalable reporting solutions using Power BI, Tableau, or Qlik Sense, and processes large multi-asset datasets with Python, PySpark, and SQL. Automates reporting, integrates APIs and financial data providers, and collaborates with investment and technology teams to support portfolio management and investment decisions.