Bio

Curiosity driven data science leader and strategist. More than 20 years of industry experience in data modeling and quantitative development. * AWS SageMaker, AWS Fraud Detection * Published work in Biologically Inspired Computation * Published work in LOD (https://lod2020.icas.xyz/), best talk award * Developed and launched an innovative ML product based on genetic programming in the retail space * Applied latest Python libraries: TensorFlow and Keras for neural nets and deep learning * LTV Forecast for e-commerce leveraging Poisson and Pareto Distributions * Fraud Detection with Auto-encoders and variational auto-encoders * Built Recommendation Engines * Data Mining; SVM, Classification algorithms, Locality Sensitive Hashing for text clustering. LIRE and Solr integration. * Advanced knowledge of Apache Pig, Hive and Hadoop * Elastic Search for text search and Kibana, Graph to visualize. * Concurrent software systems, multi-tiered application architectures. * Sun Certified Java Programmer. * Hands-on software architect and developer experienced in software development lifecycle including design, coding, testing and maintenance of applications. * Highly proficient in Applied Mathematics: Probability theory, Differential Equations. * Expert user of Matlab and R * Reverse-engineering of trading algorithms for Forex. * MA degree in Applied Mathematics from UCLA + 3 years in PhD program in Applied Mathematics at UCLA. Area of concentration: Probability Theory, Percolation, Differential Equations. * Interests: Mathematics, Finance, Chess, Sailing and Tennis. MATHEMATICS: Research in applied mathematics, including probability theory (Central Limit Theorem, Random Walks, Stopping Times, Martingales, Markov Chains, Domino Tiling), percolation theory, applied differential equations (shock waves), real analysis (Measure Theory), combinatorics, fluid dynamics.