.The Tribe "Prozis is a powerhouse product developing company. Every day we make new products. That is only possible because we developed our own proprietary technology that ensures that we bring you high quality, beautiful and fair priced products. We endure in our philosophy of a 4.0 vertical process, manufacturing in our own facilities or with the help of our superpartners. We do everything: idea, concept, design, manufacturing, quality control, marketing, sales, logistics, printing, distribution, client support, software development, photo, video, 3D and philosophy. We deliver wherever you are, whenever you want. We don't compromise. We breathe technology, drink design and feed on our will to exceed ourselves making the best products in the world. This all starts in 2007 with a crazy guy in a garage that thinks he can change the world for the better. Right now, we are hundreds, going to thousands of crazy but focused people. Will is a skill. There is a lot of people that want to buy us out. We don't have a F****** price tag. It's not about the money. It's about our mission. Trust us. We will feed your body and mind with everything you need to exceed yourself." - miguel milhão The Team Prozis is growing and Data is flying everywhere, do you think you can catch it? Prozis Data Analytics Team collaborates with multiple business stakeholders, including C-level, and has a value-driven proposition in the company. The Role As a Business Data Scientist, you will be working in a multitalented team and your role will be analyzing large amounts of data, diving deep to identify business insights and opportunities, design simulations and experiments, developing statistical and ML models by tailoring to business needs, and collaborating with other Data Scientists, Data Analysts, Business Intelligence Engineers and Data Engineers. You will be responsible for the following topics: Explore, clean, manipulate and analyze valuable data from different data sources with SQL, Python, Scala or equivalent; Translate product objectives to data science problems and vice-versa; Design and build modelsto improve the overall customer experience and to guide business decision making; Proactively perform data exploration to uncover future opportunities