Our journey from founding Sigmoidal back in 2016 wasn't always easy, as we met many new challenges. But we pushed through, stayed passionate about data science and machine learning, and stuck to our premise - revolutionize Data Science and Machine Learning, which motivated us to constantly reinvent ourselves. We wanted to innovate and reinvent - allowing our team to do things differently. It gave us the uncanny ability to engage with our clients and go far beyond traditional cooperation.
People at Sigmoidal share both data science and engineering backgrounds. Apart from actively engaging throughout many projects, many of them occupy a position at top technological universities, most of them holding PhDs. Combining those fields adds a lot of value in return - connecting data science and engineering, enabling us to understand machine learning models deeply and set up uniform data structures throughout.