Project Management - saeed349/quant_infra GitHub Wiki

Leading a compact team comprising data engineers, software engineers, and researchers presents its challenges, especially when managing multiple projects. To streamline these endeavors, I rely on a robust project management and documentation tool. Currently, my tool of choice is Azure DevOps, a preference that has evolved from prior use of Asana and Jira. The platform's features, such as the Kanban board and the ability to establish Sprint cycles, add an element of excitement to our workflow.

Beyond its conventional application as a project management tool, I leverage Azure DevOps extensively for documentation purposes. Its versatility allows for a seamless integration of project management and documentation processes.

My approach emphasizes minimizing requirements whenever possible. I develop solutions based on immediate needs and only invest time in creating templates when repetition becomes necessary. The strategy revolves around swiftly building Minimum Viable Products (MVPs), followed by iterative development and incremental improvements. Code standardization is introduced judiciously, identifying areas for improvement during the development process. Documentation is a continuous process throughout iterations. Contrary to the common practice of extensively documenting code in the initial iteration, I recognize the importance of adapting documentation to the evolving requirements observed in each Sprint cycle. This adaptive approach ensures alignment with the dynamic nature of evolving project.

For individuals embarking on the journey of building a quantitative strategy or engaging in quantitative research, the key lies in moving swiftly and embracing the process of trial and error. The pursuit of creating a flawless platform from day one is an unattainable goal unless one has prior experience. Therefore, the emphasis should be on continuous, iterative improvement.