Nowadays, 'Big Data' is one of the main topics in the data science world, and data scientists are often at the center of any organization. The benefits of becoming more data-driven are undeniable and are often needed to survive in the industry. Vertica was the first real analytic columnar database and is still the fastest in the market. However, SQL alone isn't flexible enough to meet the needs of data scientists. Python has quickly become the most popular tool in this domain, owing much of its flexibility to its high-level of abstraction and impressively large and ever-growing set of libraries. Its accessibility has led to the development of popular and perfomant APIs, like pandas and scikit-learn, and a dedicated community of data scientists. However, Python only works in-memory for a single node process. While distributed programming languages have tried to face this challenge, they are still generally in-memory and can never hope to process all of your data, and moving data is expensive. On top of all of this, data scientists must also find convenient ways to deploy their data and models. The whole process is time consuming. VerticaPy aims to solve all of these problems. The idea is simple: instead of moving data to your tools, VerticaPy brings your tools to the data.