Ian Mbaya

As a highly adaptable and skilled data science professional, I possess a robust foundation in programming, software development, data analysis, visualization, statistics, artificial intelligence, agile practices, and technical documentation. I have a proven track record of leveraging creative and innovative solutions to drive business insights and deliver strategic solutions. My work is characterized by a deep commitment to continuous learning and improvement, as well as an adeptness at navigating complex business problems using data and technology.

IT Student Worker, GVSU Surplus Store, 11/2022 - 04/2023

1. K-Nearest Neighbor (KNN), Built a KNN algorithm from scratch using NumPy and Pandas libraries to predict blinded bird species for a citizen science project.

2. Non-Negative Matrix Factorization, Built an NMF algorithm from scratch for multi-modal prediction of protein markers (ADT) given gene expression (RNA).

3. Recurrent Neural Network (RNN), Implemented an RNN algorithm using base Python and the PyTorch Library to predict handwritten digits from the MNIST dataset with a 98% accuracy.

4. Diagonal Integration, Used PyTorch & Sklearn libraries to build a model for predicting gene expression from protein markers, without corresponding protein markers for training data., GitHub