Jarrett Spiro

Background

About Jarrett Spiro

I am a data scientist and researcher with over 25 years of programming experience (e.g, Python, PySpark, STATA, etc.) and over 20 years of experience analyzing large, structured, semi-structured and unstructured databases. Due to my deep knowledge of data analytics and great skill at communicating complex, technical concepts to a non-technical audience, I was one of two people chosen to lead Humana's Reverse Mentoring Program. Initially, we met with the CEO once a month to teach him analytics, and based on the overwhelming success of those meetings, the CEO expanded the program to include the entire Management Team (the CEO and all of his direct reports).I have extensive experience building machine learning and deep learning-based predictive models to improve customer service functions and optimize healthcare processes. I built the models in Python using Tensorflow, Keras, and Scikit Learn and PySpark using MLLIB and ML.As a researcher, I produced several insights, including: how to increase team performance, identify social network structures that foster innovation and creativity, and provide improved frameworks for organizations to make sense of their environment, increasing the organizations’ effectiveness and efficiency. Specialties: • Generative AI (Google ADK, LangGraph, OpenAI API, Langchain, RAG, Transformer Reinforcement Learning, Huggingface)• Data analysis• Python (including keras, tensorflow, pandas, scikit-learn, nltk, networkx, numpy)• PySpark (including ML, MLLIB, SparkSQL)• Hive• SQL (MySQL, Microsoft SQL, Oracle SQL, etc.)• Social Network Analysis (UCINET, Pajek, Gephi)• STATA• Machine Learning (Decision trees, Random Forest, SVM, Random Forests, Gradient Boosting, etc.)• Deep Learning (Convolutional Neural Networks, Recurrent Neural Networks, Generative Adversarial Networks, etc.)• Econometrics and Statistics (Linear Regression, Logistic Regression, Structural Equation Modeling, Time Series, Hazard Rate Analysis, Qualitative Case Analysis, etc.)• Agent-Based Computer Simulations