Phillip Jones' Resume
Seeking opportunities in Machine Learning and Data Science
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American Fidelity Corporation
Data Scientist: 2022 to Present
As a subject matter expert and consultant at American Fidelity Corporation, a diverse holding company owned by the Cameron Family, I engage with a wide range of subsidiary companies, including American Fidelity Assurance, Woligo, Insurica, APL, FFGA, First Fidelity Bank, the Dallas Wings (WNBA team), Panther City Lacrosse team, and various property companies. My role exposes me to multiple company structures and involves working on a variety of projects, providing expertise and support across different sectors to ensure dynamic and impactful contributions.
In this capacity, I have developed and deployed GPT baseds LLM that functions as an internal chatbots and personal assistants, enhancing task efficiency. I utilized SAS and DataRobot to create a ‘red flag’ predictive model, proactively identifying potentially fraudulent claims. Additionally, I developed mobile and web applications using Django, Python, Flutter, and Vue.JS, significantly improving automation and reducing task times by tenfold.
My work also includes leveraging machine learning for complex problem-solving, such as using XGBoost Classifier to predict underfunding in imbalanced datasets for lead generation and employing advanced methods like Box-Jenkins and neural-Prophet for production forecasts to optimize staffing models. I have constructed data ingestion pipelines for ticketing automation and dashboards for our sports teams, the Dallas Wings and Panther City LAX, and built and maintained PowerBI dashboards for various projects.
Furthermore, I have successfully created and maintained a pipeline for a ‘public data lake,’ serving curated data to clients across multiple industries, including sports, real estate, banking, and insurance. My continuous updates of deployed models via automated pipelines ensure our solutions remain accurate and relevant.
This role has let my explore a wide range of disciplines such as data science, machine learning, data engineering, and software engineering.
Chesapeake Energy
Scientist: 2014 to Present
Impact business decisions by designing analytical programs to address challenging problems
Developed neural networks (SOM and MLP) for prediction of geologic facies from wireline data
Developed Random Forest regression algorithm for predicting clay species from wireline data
Utilized PCA and k-means clustering for development of chemofacies detection algorithm
Develop software applications utilizing LabVIEW and Python
Built and maintained Spotfire visualizations for a variety of analyses
Data mining across disparate datasets for integration into reservoir assessment projects
Stim-Lab
Laboratory Technician: 2009 to 2014
Collaborated with scientists and engineers gather and analyze data for reports
Enhanced delivery of visualizations of samples in reports for clients and consortium presentations
Streamlined methods used in core flooding procedures
Optimized sample preparation to reduce time devoted to sample preparation
Education & Skills
Always growing
Western Governors University, M.B.A IT Management
2023 to Present
Western Governors University, M.S. Data Analytics
University of North Dakota, B.S. Interdisciplinary Science