Konrad is a Software Engineer, leads the Automation an Architecture team and is working on the digital transformation.

Thank you for the discussion during the global meeting. This token commemorates the occasion. DS3, Strategy & Venturing Major

Working as a Scrum Master in Alyce project and Process Manager for DisQus, Product owner for few Clinical Operations SharePoint sites.

Data Acquisition Technology Expert (Associate Director) at Bayer Healthcare Pharmaceuticals

I'm part of DS3 group and I work as Process Manager for Technology Application Management

Sai works at Bayer Pharmaceuticals R&D as SVP, Head of Data Science & Artificial Intelligence, DS&AI. His previous experience includes working at GSK, AstraZeneca and Deloitte. Please contact him for any question you may have or just want to engage on any fun topic.

The Applied Machine Learning Group (AML) strives for the application of a data-driven approach to drug research and development by developing and utilizing best-in-class machine learning (ML) models to optimize R&D processes. The implementation of ML algorithms accelerates drug discovery and a platform to monitor and self-train models enables portfolio view of our capabilities, allowing us to become more focused. We envision to work in a fast-paced setting, we expect to fail quickly and adapt swiftly, all while expanding your ML capabilities. We also believe in making the right choices not only for our immediate team but decisions to build solutions catered to broader R&D. The success at AML will be measured by bucketing the benefit of the developed capability into one or more of these three buckets, (1) Savings in time (2) Savings in cost (3) Generation of new insights

ChemogenomicsDB (CGDB) and Älixir are prime examples of creating data assets and insight solutions to help improve digital and data capabilities, enhance scientific productivity, and invigorate early pipeline. Using our products, Bayer R&D colleagues can - access to a broad range of data assets essential for solving key drug discovery questions - explore integrated biomedical and chemical data for scientific curiosity, inspiration, and knowledge discovery - generate insights with the assistance of interactive visualizations for evidence-informed decision making