- Healthcare & Life Sciences
- Pharmaceuticals & BioTech
- Private Equity
- Professional Services
Christopher Hayduk is a data scientist and solutions architect at SFL Scientific. In this role, he provides strategy, direction, and technical development for operational and R&D groups that focus on applied data science and rapid prototype methods. Combining his experience in math, science, and data analytics with a passion for translating the language of machine learning and innovation into approachable, real-world applications, Chris identifies technical strategy and project design and leverages design thinking approaches.
Prior to joining the team at SFL Scientific, he earned a Master’s in Mathematics from The City College of New York and a Master’s in Applied Statistics from Fordham University’s Gabelli School of Business. Chris is passionate about understanding the theory behind machine learning models and using this knowledge to select the best analytics tools possible for clients. His main interests lie in natural language processing and computer vision, having done previous work in mathematical linguistics and CNNs applied to biometric data.