Financial Analyst (50%-80%)

You will act as the key liaison between investment operations, risk management, and data engineering, ensuring accurate and timely integration of multi-asset portfolio data into downstream risk and reporting environments. This role demands regular, proactive engagement with customers to understand their financial objectives, present findings, and collaborate on strategic recommendations.

• Lead the maintenance and enhancement of RiskHub and PORT adAPPter for risk data integration, ETL workflows, and reporting processes.
• Model and map financial instruments and portfolios for integration with external risk and performance platforms (e.g., factor models, benchmarks).
• Maintain and extend the Python codebase powering internal tools, including data ingestion logic, validation routines, and configuration GUIs.
• Oversee database design, schema migrations, and optimization of portfolio-level and position-level data storage.
• Collaborate with business users to support workflows for instrument resolution, portfolio setup, and reporting configuration.
• Troubleshoot data integrity issues and ensure robustness of end-to-end ETL chains.
• Articulate complex financial conepts clearly and effectively to diverse audiences, both written and verbal
• Understand and meet customer needs, building strong relationships through effective communication and proactive support.

• Higher education degree in a quantitative field. Relevant certification (e.g. FRM, CFA preferred)
• 5+ years of experience in a related professional field
• Solid understanding of financial instruments, including equities, bonds, derivatives, and FX products.
• Prior experience working with portfolio data modeling in the context of risk, compliance, or performance systems.
• Familiarity with one or more of the following risk analytics environments:
• Bloomberg PORT
• MSCI BarraOne
• Axioma or equivalent platforms
• Experience with performance reconciliation frameworks, integration of benchmark data, hedging overlays, and NAV-based reporting.
• Strong Python programming skills, including:
• Data processing with pandas
• ORM-based modeling using SQLAlchemy
• Experience with internal tools or dashboards built in Dash or equivalent beneficial
• Proficiency in SQL and relational databases, particularly:
• Microsoft SQL Server
• PostgreSQL
• Experience designing or maintaining ETL processesand supporting data validation pipelines in a production setting.
• Familiarity with documentation and reporting frameworks (e.g., Sphinx, Quarto, Excel-based reporting layers).