Investment Data Analyst

Analyst, Investment Operations | Houston, TX | Investment Management

• Company Overview
• A leading global alternative asset manager is seeking an Analyst to join its Private Credit Investment Operations team in Houston. The firm manages capital on behalf of a sophisticated institutional investor base and invests across private and public credit strategies.
• The platform specializes in complex credit and structured capital solutions and offers exposure to strategies including private lending, special opportunities, and significant risk transfer (SRT).

You will work with large and complex investment datasets, help automate recurring processes, build tools and reporting solutions, and partner closely with Investment, Finance, Technology, Fund Accounting, and external administrators.

• Key Responsibilities
• Investment Operations
• Support daily operational processes including trade settlement, collateral management, asset servicing, and reconciliations
• Manage trade capture and reconciliation processes and investigate exceptions through root-cause analysis
• Maintain and validate investment datasets used for performance, risk, portfolio management, and client reporting
• Monitor deal pipelines and support operational readiness for new private credit investments
• Assist with funding execution, liquidity management, and cash coordination
• Partner with fund accounting teams and third-party administrators to validate NAV and P&L components
• Support monthly close processes and recurring investment reporting
• Ensure investment activity is accurately reflected across internal systems throughout the investment lifecycle

• Data, Python & SQL
• Use Python and SQL to analyze, reconcile, validate, and manipulate investment and portfolio data
• Write and maintain SQL queries to extract and analyze data across investment and operational datasets
• Develop Python scripts and tools to automate manual and recurring operational processes
• Build automated checks to identify data discrepancies, exceptions, and potential operational issues
• Analyze large datasets to investigate breaks and perform root-cause analysis
• Assist in developing scalable data workflows supporting investment operations and reporting
• Work with Technology and investment teams to improve data quality, accessibility, and reporting infrastructure
• Help replace manual Excel-based processes with more scalable Python-, SQL-, and data-driven solutions
• Contribute to dashboards, internal reporting tools, and other technology initiatives supporting the investment platform

• Cross-Functional & Process Improvement
• Partner closely with Investment, Finance, Technology, Fund Accounting, and other internal teams
• Identify opportunities to automate and improve existing investment operations workflows
• Contribute to the development and enhancement of internal tools, systems, and data infrastructure
• Assist with ad hoc investment, operational, and data analysis
• Develop a strong understanding of how private credit investments flow from deal execution through funding, servicing, accounting, and reporting

Qualifications

• Required
• Bachelor’s degree in Finance, Accounting, Economics, Computer Science, Data Analytics, Engineering, Mathematics, or another quantitative/technical discipline
• Recent graduates and candidates in the first few years of their careers are encouraged to apply
• Hands-on experience with Python and SQL through professional experience, internships, coursework, or personal projects
• Ability to write SQL queries and use Python for data analysis, manipulation, or automation
• Strong Excel skills and comfort working with large datasets
• Strong analytical and problem-solving capabilities
• Exceptional attention to detail and a strong sense of ownership
• Ability to investigate data discrepancies and work through problems independently
• Ability to manage multiple priorities in a fast-paced environment
• Clear and concise communication skills
• Genuine interest in finance, investing, private credit, data, and financial technology