Portfolio Analytics Architect

A Portfolio Analytics Architect is responsible for leading the data validation process end-to-end for data conversion projects. The ideal candidate will have a strong understanding of financial portfolio data, a motivation to work on data problems, strong analytical and communication skills and the ability to deliver results in adherence with project deadlines while meeting high quality standards. They take a hands-on approach to solving problems, build scalable and automated solutions, work collaboratively with project teams across regions and take ownership of the outcomes our clients depend on.

Applicants must have legal authorization to work in the country where this role is based on the first day of employment. Visa sponsorship is not available for this position.

• Develop scalable data analytics processes for validation in Databricks 
• Write custom Python logic to detect large-scale data anomalies and automate remediation
• Build and maintain reusable validation tools, runbooks and documentation that scale across projects
• Prepare validation findings, discrepancy analysis and status materials that keep each data validation project on track through to completion
• Research and identify portfolio data performance discrepancies, determine root causes and recommend how best to fix manual data issues
• Review, compare and document system calculation methodologies differences
• Coordinate across global project teams and time zones, communicating regular status updates for assigned data projects while effectively setting expectations
• Mitigate project risks by effectively escalating key impediments to project leads and management
• Prioritize and context-switch effectively to complete simultaneous projects; seeing each through to the finish line
• Identify and implement AI-driven automation and LLM integrations to streamline implementation

• Bachelor’s degree in Finance, Mathematics, Statistics, Engineering, Business, Economics or a related field; CFA or FRM progress is a plus
• 2+ years experience working in Technology, Finance, Consulting, fund accounting or investment operations
• Hands-on experience working with complex investment datasets, including multi-asset class portfolios, performance data, and market data from various sources
• Proficiency in Python, Spark, and/or SQL with familiarity of ETL fundamentals
• Working knowledge of REST APIs
• Experience with Databricks and/or a cloud-based distributed data platform
• Solution-oriented approach and a passion for problem solving
• Proven ability to research, design and implement solutions for complex problems
• Positive attitude, strong work ethic, proactive and a high contributing team player
• Independent, adaptable and can thrive in a fast-paced environment
• Clear written and verbal communication skills, with the ability to document complex findings and work effectively with colleagues across time zones
• Able to work hours that regularly overlap with teams in the US and UK