Data Analyst

About Our Client

Our client is a well-established private investment firm focused on providing flexible, asset-based financing solutions to growing businesses across a range of industries. With a collaborative, entrepreneurial culture and a disciplined investment approach, the firm partners with companies at critical stages of growth by delivering customized capital solutions. Backed by an experienced leadership team and a strong track record of deploying billions in capital, the organization offers employees the opportunity to make a meaningful impact while working alongside accomplished investment and technology professionals.

About the Role

Our client is seeking a

Data Analytics, Risk Management

professional to join its Asset Management team. Reporting to the Director of Asset Management, this individual will play a key role in managing and analyzing portfolio data while serving as the bridge between Asset Management and Technology. This position is ideal for someone who enjoys solving complex data challenges, building scalable processes, and leveraging analytics and automation to support investment decision-making and portfolio risk management.

Responsibilities

• Own the end-to-end extraction, validation, mapping, and management of collateral and portfolio data from multiple borrower and servicing sources.
• Develop and maintain automated data pipelines and ETL processes using Python and SQL while identifying opportunities to improve data quality and operational efficiency.
• Partner with Technology teams to define business requirements, support centralized data platform initiatives, and contribute to system design and testing.
• Build reporting, dashboards, and analytical tools that provide actionable insights into portfolio performance, collateral trends, and risk metrics.
• Support borrowing base reviews, monitor portfolio compliance, and maintain clear documentation for data workflows, field mappings, and business processes.

Requirements

• Bachelor's degree in Finance, Computer Science, Data Science, Engineering, or another quantitative discipline.
• 3\+ years of experience in asset management, private credit, structured finance, investment banking, or a related financial services environment.
• Strong technical skills in Python and SQL, with experience developing automated data extraction, transformation, and reporting solutions.
• Experience working with large, complex financial datasets, data mapping, cash flow modeling, and AI-powered document extraction tools or LLM APIs.
• Excellent analytical, communication, and organizational skills with the ability to thrive in a fast-paced, collaborative environment.