Data Analyst | M.S. Data Science Candidate at Boston University
My journey into data analytics began at UC San Diego with an elective C++ introductory course and has since evolved into a deep-seated passion for leveraging Python, TensorFlow, and other cutting-edge technologies to solve complex, real-world problems. I've grown from automating Excel tasks to building sophisticated algorithms and data models. A notable achievement includes developing a convolutional neural network with a 93% accuracy rate for geological image classification. Although I have mostly been a self-taught programmer, Boston University is fueling my ambition to not only refine my self-taught skills with formal education but also to explore the possibility of furthering my education with a doctorate. My goal is to use my data science expertise to make a tangible impact in whatever field or job I find myself. I look forward to applying my diverse skills and experiences in an environment that appreciates innovation, creative problem-solving, and enthusiasm.
My capstone data science project and various other projects completed during my time at Boston University in order from most recent to oldest. All accompanying code for these projects can be found in the appropriately named repository.
- Boston University M.S. Data Science Capstone Project
- CS 544: Statistics and Probability
- CS 555: Foundations of Machine Learning
- CS 699: Classification Algorithms
Most of the code used for these projects was property of the company I was working for at the time and therefore I'm unable to share publicly. All accompanying code I'm able to share can be found in the appropriately named repository.
- Maxon Consulting
- illumina
- Oncology Assay QC Work Instruction: A quality control experimental procedure I drafted to test illumina's Oncology product Nextera XT.
- BlueJeans
- Customer Success Dashboard: My first data science project ever. A customer success dashboard that utilized Java and Google BigQuery to query customer data and display KPIs for the sales team.
Underconstruction. Adding miscillaneous projects I have worked on as a consultant or as a learning exercise.
- AI
- Python
- Machine Learning