Ramon Perez
Hello! I'm Ramon, a data scientist, researcher, and educator living in Sydney. I currently work as a Senior Product Developer at Decoded, where I create custom data science tools, workshops, and training programs for clients in industries ranging from retail to finance. My previous roles have been at the intersection of education, data science, and research in the areas of entrepreneurship and strategy, alongside a few research ventures in consumer behavior and development economics in industry and academia, respectively. During my professional career, I've had the fortune of working with research teams dedicated to helping multinational companies understand their customers better via data-driven approaches ranging from A/B testing to machine learning. I also enjoy giving workshops and have had the honor of participating in PyCon (US, APAC, and Chile), SciPy (US and Japan), and countless Meetup events. In my spare time, I enjoy cycling, playing baseball, and exploring many of the outdoor wonders Australia has to offer.
Sessions
Programmers, regardless of their level of experience, enjoy solving increasingly complex challenges within their domains of expertise, and one of the main reasons they can spend more time working on different challenges is because of the workflows they put in place around their projects. Data Engineers build pipelines to make sure the company's data is in optimal condition for Analysts to answer business critical questions, for Data Scientists to automate the selection, engineering, and analysis of distinct features before training models, and for machine learning engineers to know where to get data from, or send it to, for the APIs they build. On the other hand, developers automate the infrastructures of software products to reduce time to market of new features. These groups of data professionals and engineers are not too foreign to each other as they all speak the same language, Python. That said, the goal of this workshop is to dive deep into different workflow patterns for building pipelines for data and machine learning projects. In other words, this workshop bridges the gap between building one-off projects and building automated and reusable pipelines, all while creating an environment that welcomes both, newcomers and experts to either the data and machine learning fields or the engineering one.