Caroline Sieger Fernandes is a Customer-Facing Data Scientist with DataRobot where she focuses on providing data science knowledge, expertise, and advisory to customers across industries to enable them to meet their AI and Machine Learning goals and achieve measurable business value. She has a master’s degree in applied mathematics from Clemson University where she specialized in sparse and inverse problems. Prior to joining DataRobot, Caroline’s experiences included working for MIT Lincoln Laboratory in Boston developing self-separation and collision avoidance algorithms for unmanned aerial vehicles, work at Ecole Polytechnique Fédérale de Lausanne (EPFL) in Switzerland to improve ankle joint replacement devices, and partnering with Co-CEOs of a boutique management consultancy start-up in London to navigate the company through rapid 3x growth to develop strategic plans and use data to run the business.