Fueled by a passion for biotechnology, my engineering expertise, solid grounding in mathematics and statistics, along with mastery of programming and machine learning, positions me as a key contributor within any team.
I view programming, data science, wet lab biology, and statistics as essential skills for tackling challenging problems. Competency, and ideally mastery, opens doors to new levels of creative thinking.
Wet Lab Biology
Understanding how to collect data and the nuances of different techniques has implications for data science and offers a different perspective to problem solving
focused tasks.
Statistical Inference
Traditional and Bayesian statistics is key taking a problem from a research to exploration to a sound data supported decision
Machine Learning
An understanding of Gradient Boosting, SVM, PCA, and many other unsupervised/supervised techniques is crucial for data science.
Production-Grade Programming
Writing clean and concise programming is key for dropping barriers to collaboration
Graphic User Interface Development
Using Python, HTML, and CSS to create beautiful front-end interfaces
Deep Learning
Building and deploying neural networks focused in biotechnology