Senior Quality Assurance Analyst

An AI-native Asset Management firm based out of Singapore is looking for a QA Analyst / Business Test Manager to support development and testing of a data-intensive financial technology platform. The ideal candidate will bridge the gap between technical testing and business logic — able to understand functional requirements, design and run tests, and help explain or troubleshoot system behaviour.Role: Prior experience in asset management, investment research, or portfolio construction/optimisation is strongly preferred. The candidate should be comfortable interpreting the outputs of models and analytics used in real-world investment workflows.This is a hands-on role involving Python, data analysis, and structured test design, with some exposure to client-facing queries and platform support.Responsibilities:Design and maintain test plans and regression suites (manual and automated)Understand application workflows and business rules across rebalancing, performance, andreporting modulesInvestigate discrepancies in data or attribution output using internal tools and queriesDocument and maintain functional requirements and test coverage as the platform evolvesCollaborate with developers to validate features and debug edge casesSupport internal and external users by explaining or investigating system behaviorEssential experience:Proficient in Python (data validation, scripting, test harnesses)Strong SQL skills (PostgreSQL preferred)Familiarity with Unix-style command-line tools and shell scriptingUnderstanding of structured software testing (regression, acceptance, edge cases)Experience with test management tools and practicesComfortable working across CLI-based tools, Git, and internal documentationInfrastructure & Data Ecosystem:Experience with AWS (EC2, S3, etc.)Understanding of modern database systems — data warehouses, data lakes, etc.Basic comfort working with large datasets and file-based formats like ParquetPreferred:Experience working in asset management or investment platformsFamiliarity with investment research workflows, portfolio construction, or optimisation techniquesUnderstanding of financial datasets such as holdings, returns, attribution, and benchmark-relative performance