Paul Stolorz Email Address

Chief Data Scientist

App Annie provides business intelligence solutions such as ranking, sales analytics and advanced market intelligence for the app economy.

Accomplished technology executive and entrepreneur. Successful track record of launching and driving online businesses with a strong product and service culture, and managing revenue growth up to $30 million run rates. Data Science - Built and managed multiple Data Science organizations in high performance start-up and enterprise environments, with an emphasis on Machine Learning at scale. - Verticals and Applications supported: predictive analytics for targeted marketing; recommendation engines; fraud detection; social media and social network analysis; system health maintenance; natural language search and retrieval; bioinformatics; extreme scale image DB's Data Infrastructure and Services - Big, Little and Medium Data (there's plenty of value in the middle); visualization; data warehousing; reporting; real-time analytics; ETL; BI strategies; data modeling; distributed infrastructure; Hadoop; Mapreduce; R - Best Practices: A/B testing frameworks; dashboards and performance metrics; SLA management; latency reduction; campaign management; analytics integration with business workflows Algorithms - Deep practical expertise with the usual machine learning and statistics suspects at scale: - clustering (hierarchical, K-means, EM); logistic regression, decision trees and forests; SVM; SVD/PCA; Bayesian fu; neural nets; NLP; Boltzmann machines and deep learning; Markov models, hidden and otherwise; MCMC methods People - Recruitment & motivation of Data Science & Big Data teams embedded in the enterprise - Cultivation of product & service culture emphasizing client needs along with technical excellence - Mentoring processes enabling team scaling from 1 to 100 Specialties: Building and supporting quality products, growing high-performance teams, investor fund-raising, sales, client management, building products, data mining and data science, machine learning, distributed computing infrastructure - did I mention building products?