Our goal as scientists is to generate and disseminate new knowledge to the public. In data science, we face several challenges, including a fast-paced working environment, constantly changing data sources and tools, project life cycles that can last weeks to years, and many times working as individuals or small teams. To make our results reproducible and understandable, we need to have an efficient and flexible organizational strategy. Here I present various techniques and pitfalls I have encountered in my ten-year career in data science. This talk is aimed at people new to the field but is a valuable discussion for veteran data scientists.