Stefania Sokolowski

Principal Data Scientist at Memorial Sloan Kettering

Bio

Stefania Sokolowski is a Principal Data Scientist within the Applied Data Science team in the Strategy and Innovation division at Memorial Sloan Kettering Cancer Center. In her current position, she leads analytics and machine learning projects, working directly with stakeholders to ensure a smooth execution. Stefania also mentors and manages a team of data scientists.

Stefania has worked in the data science and healthcare industries for 10 years. Her areas of expertise include the translation of business problems into analytics, data exploration and visualization, predictive modeling, and data products. She is known for solving hard and vague business problems by deploying a “practical approach” to data science, which includes building quick and simple prototypes, models, and analyses; then iterating to maximize value and usability.

Stefania has a M.A. in Cognitive and Neural Systems and B.A. in Neuroscience from Boston University.

Track: Implementing Analytics

Why We Should KISS More In Healthcare

Data scientists often want to use the latest and most sophisticated models and technologies to solve business problems, thinking that the more complicated, the better. However, applying the design principle of “Keep it simple, stupid” (KISS) can result in quicker value to stakeholders/users, less resources used, and increased application of analytic insights and user tool adoption. KISS is particularly useful in the high-stake healthcare setting where data analytics and science utilize sensitive medical information and often affect patient care delivery. This presentation will go through a few examples of data science/analytic projects at Memorial Sloan Kettering Cancer Center that demonstrate the value of KISS.