Andrew Huang

OVERVIEW: Exceptionally fluent in using Python for data wrangling, ingestion, analysis, and visualization.

PYTHON PACKAGES: Significant experience using pandas, xarray, matplotlib, and holoviews (able to use most of the library effectively from memory); proficient using dask, numpy, metpy, and scipy (able to use essential functions from memory); and familiar using many other packages like geopandas, rasterio, numba, datashader, and flask (aware of its capabilities, but may need a quick refresher).

EDUCATION: Bachelor's and Master's in atmospheric sciences with a focus on model comparison and verification; knowledgeable about various deterministic and probabilistic metrics such as RMSE and Brier score in addition to significance testing.

OPTIMIZATION: Experienced in optimizing code through numpy vectorization, dask parallelization, numba compilation, and/or straightforward code cleanup and reordering; previously sped up code runtime by a factor of 40 through these techniques.

OPEN SOURCE: Made over 200 open source GitHub contributions and 20 merged pull requests within the last year, thus accustomed to git, PEP 8, unit testing, and CI tools like pytest and Travis. Contributed primarily to holoviews and xskillscore, but also xarray, metpy, cartopy, geoviews, and panel.

FILE FORMATS: Developed an open source package for animating data named ahlive. Skilled in wrangling many data formats: plain binary, GRIB, HDF5, netCDF, GeoTIF, JSON, YAML, and csv. Worked with PostgreSQL and sqlite databases.

DATA VISUALIZATION: Versed in visualizing large amounts of data and the different types of plots: heatmaps, histograms, scatter, and violin plots for example.

DEVOPS: Some DevOps experience in automating deployable code using Terraform, Ansible, Airflow, Jenkins, and Docker.