Jonathan Evans Email & Phone Number

Killeen, Tx, Us

• Led the development of a Random Forest predictive model for e-commerce fraud detection, using characteristics like IP address, number of previous orders, and credit card zip code to reduce the number of fraudulent orders by 93%.• Engineered an advanced in-house chatbot leveraging vector embeddings and retrieval-augmented generation (RAG) on Azure Cloud OpenAI, encapsulating cutting-edge AI within a user-friendly Streamlit interface. This innovation not only served as a robust proof of concept but was also fully adopted by the company, leading to a noteworthy enhancement in overall operational efficiency.• Employed Python (along with TensorFlow, Langchain, Keras, and Transformers) to integrate and utilize the deepset/roberta-base-squad2 model for developing a responsive question-answering feature within an AI Document Summarizer and Question Answering Tool that increased product research speed by 43%, showing a deep understanding of NLP models for interactive applications.• Utilized propensity score matching (with the Python ‘causalinference’ library) to validate causality between increased ad spending and click rates, showcasing expertise in advanced causal inference techniques to derive meaningful insights from marketing data.• Implemented A/B testing methodologies (using scipy.stats and statsmodels) to compare outcomes with varied ad spending levels and content types, providing a structured approach to evaluating marketing strategy effectiveness and reducing misdirected ad spend by over 75%.• Implemented strategic process enhancements, including the development of real-time KPI dashboards (using Tableau) and automated data pipelines (by utilizing Python, GCP, Facebook Marketing APIs, and cron jobs), which expedited decision-making, reduced operational lag, and streamlined tasks from ad creation to customer service.

• Spearheaded the strategic planning and execution of a data pipeline, employing Amazon Athena for data querying, and developed innovative dashboarding solutions to streamline data acquisition and improve efficiency and accessibility.• Utilized Python to execute rigorous statistical tests for analyzing complex survey data, employing software tools and numerous libraries (pandas, scikit-learn, statsmodels, etc.) for statistical analysis and visualization to generate insights, contributing to research publications that enhanced the company's educational sector profile.• Led the design and implementation of a company-wide dashboarding system using a combination of Qlik and Google Data Studio, leveraging best practices in data dissemination and creating proof-of-concept dashboards that set benchmarks for quality and usability.• Key in deploying and fine-tuning a big data querying system using Amazon Athena, ensuring high data integrity and quality, and supporting sophisticated data analysis and research efforts.• Initiated and led R training sessions, enhancing the team's abilities in statistical computing and graphics, and fostering a collaborative learning environment for data-driven project execution.• Accessed and managed data within a Redshift database, skillfully utilizing and modifying the database to support complex SQL query operations for the Family Engagement team.• Executed over 50 complex SQL queries for the Family Engagement team at Panorama Education, involving intricate JOIN statements, temporary tables creation, and the use of functions such as DATEDIFF, showcasing deep SQL expertise.• Automated SQL queries using Python scripts, cron jobs, and Google APIs to insert results into a Google Sheet every Friday, showcasing advanced skills in integrating SQL with Python and task scheduling for automated data processing.

Killeen, Texas, United States

• Achieved a streamlined, organized, and production-ready architecture for a prototype ticket forecasting model, emphasizing clean code, modularity, and effective productionization techniques for scalability and maintenance.• Used analytical tools and critical thinking to analyze and determine the nature and source of over 600 organizational technical problems so they could be brought to timely resolutions (either solely by me or with help from my colleagues).• Worked with upper management and third-party vendors to build a cost-effective ticketing system to track all technical incidents, large-scale software version releases and updates, contract flows, and much more.• Boosted staff efficiency through the ground-up development of a company knowledge base that staff frequently use to take power into their own hands by diagnosing, analyzing, and resolving technical issues.• Tasked with the creation and monitoring of key performance indicators (KPIs) for the newly implemented ticketing system, methodically tracked and analyzed metrics such as average response time, daily staff support volume, and frequency of recurring issues.• Conducted in-depth EDA to uncover patterns, trends, and anomalies in historical ticket data, providing valuable insights that informed decision-making in a ticket forecasting model I built.• Developed over 30 automations that further increased the efficiency of the ticketing system and knowledge base.• Developed and maintained skill levels for desktop software and applications which include applications such as Power BI, Tableau, SQL, Putty and Powershell.

Austin, Texas, United States

• Leveraged NLTK and TextBlob for text processing tasks in the analysis of chat data, demonstrating skills in utilizing text processing libraries to prepare and analyze large text datasets.• Utilized Pandas for data manipulation tasks such as word frequency analysis, showcasing expertise in handling and analyzing data to extract meaningful insights.• Executed sentiment analysis using TextBlob on Electronic Arts' customer chat data to trace the emotional progression of conversations, identifying how shifts in sentiment influenced customer satisfaction and engagement levels.• Employed topic modeling techniques to decode latent themes within Electronic Arts' customer service chats, uncovering the primary concerns and interests that shaped user experience and drove customer interactions.• Crafted intricate visualizations using Matplotlib and Plotly to represent the findings from the NLP analysis of Electronic Arts' chat data, presenting complex behavioral insights in a clear and accessible manner to stakeholders.• Created 20+ dashboards and visualizations (in multiple release versions of Tableau) that have empowered, engaged, and informed users in an incredibly diverse array of industries around the globe.• Used popular data analytics programs, languages, and tools (ex. Hadoop, Python, Pandas, etc.) to clean, manipulate, model, and transform datasets in ways that make them understandable and engaging for users from all walks of life.• Worked on all aspects of the engineering of my skills, including such topics as performance, testing, dashboard design & tuning.• Quickly and effectively diagnosed and responded to clients’ requests regarding data integrity and functional or interactive issues in existing and future dashboards.• Reviewed code, functions, methodology, and visualizations to detect and mitigate application problems. • Developed methodologies that allowed for efficient and repetitive data extraction processes.

Master Of Science - Ms, Business Analytics

Bachelor Of Business Administration - Bba, Management Information Systems, General