I'm an interdisciplinary problem-solver with formal training in biophysics research, passion for learning, and commitment to applying the scientific method to wherever it can make a meaningful difference. I'm always seeking opportunities to utilize my skills.My interest in the natural sciences has been a guiding motivation throughout my formal education. Graduate school exposed me to the rigors of scientific research and taught me the landscape of interdisciplinary fields like biophysics: there are gems of insight from different fields that may contribute to solving the problem at hand. The system knowledge and sample preparation of biologists, synthetic magic and manipulation of chemists, quantitative instruments, models and mindset of physicists were gems I picked up from graduate school years.This has led me to data science, the fourth paradigm of science, to supplement the theoretical, experimental, and computational paradigms. Excess hype aside, there is much to be gained when we think about what we do with data generated from experiments: sharing standardized data with the community for reproducibility, leveraging negative results, and immortalizing researchers' efforts that would otherwise decay in lab silos. It's empowering to know that this paradigm extends well beyond the natural sciences to other fields of interest such as the business world, education and public health.Some new gems I've found along the path so far through projects:- Programming: Python, Git, bash- Data Engineering: PostgreSQL, database normalization, tidying data, webscraping- Modeling: Scikit-Learn's models, decision trees, Deep Learning in NLP- Statistics: assumptions in hypothesis testing, linear/logistic regression, GLMs, distributions vs. Bayesian methods- Visualization: Plotly, Dash, matplotlib, seaborn- Business Acumen: Lean Startup, Lean Analytics, Zero to One, How Google Works