Data Scientist & Researcher
I am a Data Scientist with a strong foundation in machine learning, deep learning, and data engineering. I’m experienced with a wide range of modern data science tools and techniques, and I’ve applied them across real-world projects involving AI, analytics, and automation. I enjoy transforming complex data into practical, impactful solutions and continuously expanding my expertise in advanced technologies.
I have worked on projects involving image classification, Retrieval-Augmented Generation (RAG) systems, NLP for toxic content detection, and large-scale data processing using tools such as Hadoop, Spark, TensorFlow, PyTorch, Pandas, and Scikit-learn.
Currently pursuing a Ph.D. in Computer Science at Indiana University, I previously earned a Master's in Applied Data Science and a Bachelor's in Computer Science. I thrive at the intersection of innovation and practicality—transforming data into actionable insights, efficient systems, and intelligent products that support real-world decision-making.
Download ResumeCurrently pursuing a PhD in Computer Science with a focus on Artificial Intelligence.
Completed a rigorous Master's program in Applied Data Science, focusing on machine learning, data mining, big data technologies, and statistical analysis. Engaged in projects involving predictive modeling, data visualization, and cloud computing. Developed strong skills in Python, R, SQL, and various data science frameworks.
Graduated with a Bachelor's degree in Computer Science, gaining a solid foundation in programming, algorithms, data structures, and software development. Participated in various projects and internships that enhanced my coding skills and practical knowledge of computer science principles.
As a Graduate Research and Teaching Assistant at the PhD level, I supported both academic instruction and research initiatives within the department. My responsibilities included assisting with course delivery, leading lab sessions, holding office hours, grading assignments, and providing individualized support to students to reinforce complex concepts. In parallel, I contributed to faculty research through literature reviews, data analysis, experimentation, and the development of technical materials. This role strengthened my expertise in scientific inquiry, advanced data science methods, and academic communication while enhancing my ability to explain technical topics clearly and effectively.
As a Data Scientist, I developed an AI-powered inspection system using YOLO to analyze thermal drone imagery, detect equipment, and extract temperature readings. This enabled automated identification of overheated or abnormal assets, improving maintenance efficiency and reducing failure risks. I also built a high-accuracy revenue forecasting solution using time-series models with external regressors, designing a full ETL pipeline, performing feature engineering on marketing and seasonal data, and delivering dashboards to support strategic decision-making.
As a Data Scientist Intern at Orange Côte d’Ivoire, I contributed to several innovative projects that improved operational efficiency and data-driven decision-making. I worked on an LLM-based assistant to automate HR inquiries, developed a YOLO-powered machine learning model for ID card classification, and supported revenue prediction efforts through advanced data modeling. Additionally, I collaborated on multiple ETL and data engineering workflows, ensuring reliable data integration and high-quality processing across systems.
As an Intern Analyst Programmer, I contributed to key software development initiatives and supported various technical projects. My work involved programming, data analysis, and system maintenance, while collaborating closely with experienced developers. I assisted in troubleshooting and resolving technical issues, helping improve workflow efficiency. This role provided valuable hands-on experience and a strong foundation in real-world software development practices.
As a Graduate Teaching Assistant in data science, I supported course instruction by assisting in labs, holding office hours, grading assignments, and helping develop learning materials. The role required strong communication skills and solid experience in data science, programming, and data analysis. I stayed current with best practices in data science education, including visualization, statistical methods, machine learning, and data management.
beugrecedric1@outlook.com
Indiana University / Georgia State University
jbeugre1.github.io/Portfolio
Indianapolis, IN