Profile Motivated and dynamic learner, deploying advanced data analytics techniques and machine learning algorithms to build predictive models. Proficient with the use of Python, Java, R, SAS, SQL and MS Excel. Familiar with Linux command line and Cloud Computing. Seeking summer 2020 internship opportunity in Data Science or Machine Learning domain.
Education Austin Peay State University Clarksville, TN May 2021 Master of Science in Computer Science (4.0/4.0)
University of Ilorin Ilorin, Nigeria October 2017
Bachelor of Science in Mathematics (3.12/4.0)
• Machine Learning
• Database Analysis and Design
• SAS Programming
• Predictive Analytics
• Statistics & Probability
• Data Science with Python
• Programming in Python (Data Analytics): NumPy, Pandas, Bokeh, Seaborn, Matplotlib and SciPy in Python to performed comprehensive analyses of large datasets (soccer, superstore & customer churn data).
• Statistical Analysis (R, Minitab and SAS): Use of statistical methods (hypothesis testing & confidence interval and regression models) on datasets to gain more insight before making decision.
• Machine Learning and Deep Learning algorithms with Python: Classification, Regression, Clustering, Natural Language Processing, Convolutional Neural Network, Feature Engineering.
• Working knowledge of Web programming, Java, Hadoop, Scala, Spark and Git. Austin Peay State University Clarksville, TN August 2019 to Present Graduate Teaching Assistant
• Tutored 74 students on how to use R and Minitab to analyze data and create visualizations
• Supervised and graded 39 undergraduate students as they implement 4 individual/group statistical analysis projects in a semester
BEDC Power Plc Lagos, Nigeria January 2018 to June 2019 Data Analyst
• Solved business problems in product analysis and demand planning for products and markets by deploying advanced data analytics in SQL, Power BI, and Tableau, MS Excel to clean, transform, create visualizations and made reports for 10 projects
• Scrapped data from websites and trained machine learning models using SQL and Python to model marketing strategy for new products
Projects • Customer Segmentation: Used machine learning models to forecast profit and categorize customers in an open-source data science project on Github (https://github.com/EDLAC- Algorithm/customerSegmentation) to maximize Return on Investment
• Sentiment Analysis: Did a comprehensive sentiment analysis on customers ratings and comments on consumer goods product using Natural Language Toolkit and Sci-kit learn in Python
• Image Recognition: Deployed Convolutional Neural Network using Keras and Tensorflow in Python to develop image recognition system with an average accuracy of 70%
• Recommender System: Used the concept of correlative filtering to design product recommender system
• Categorization of soccer players based on position played on the field by integrating Principal Components Analysis and K-Means model
Activities Architecting with Google Compute Engine Google Cloud on Coursera February 2020 From Data to Insights with Google Cloud Platform Google Cloud on Coursera December 2019 Machine Learning, Data Science and Deep Learning with Python Udemy December 2019 Award: 3rd Best Researcher (Science), Annual Conference, University of Lagos, Nigeria August 2017 Volunteering Experience (UNICEF and SFH sponsored project): March 2014 to February 2015 Mentored over 100 teenagers on Reproductive Health and HIV/AIDS Prevention and Care