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Peter Olapade is a seasoned data scientist with extensive experience in developing and deploying machine learning and statistical models, particularly in predictive maintenance and hydraulic fracture growth. Currently serving as Principal Data Scientist at Pinnacle, Peter has made significant contributions, including the creation of an automated outlier detection and data cleaning algorithm. Previously, at Halliburton, Peter held roles as both Principal and Senior Data Scientist, focusing on data analytic solutions, digital signal processing, and optimization techniques. Peter's earlier experience includes software development and research roles at Schlumberger, the University of Texas at Austin, and Los Alamos National Laboratory, complemented by an academic background with a PhD in Mechanical Engineering from The University of Texas at Austin and a Master's from the University of Delaware.