Marcus Diemand

Background

About Marcus Diemand

I have 2+ years of experience working as a Data Practitioner in the fields of GIS, radiology, nanotechnology, and bioinformatics—bringing natural inquisitiveness to each new field I’ve had the opportunity to encounter. As a Smart City Developer, I wore both Data Engineer and Data Scientist hats. First, developing scripts to extract both structured tabular and unstructured geospatial datasets from the city’s OpenData GeoHub using BeautifulSoup. Second, developing a cascading pipeline of Jupyter Notebooks to clean, join, and transform this data into usable features for machine learning—leaning heavily upon Pandas and Matplotlib. Third, developing an ensemble classification model with Sci-kit Learn to recommend traffic calming (speed reduction) for suburban roads considered by the Traffic Department. As a Bioinformatician/Data Analyst, I loaded metagenomics data into a MySQL database to facilitate data exploration for a biologist client. The data (bacterial phylogenies output from the R-based Tuxedo Suite on a local Unix compute-cluster) could be queried along taxonomic ranks and would give the biologist—hoping to locate water pathogens—the ability to drill up and down phylogenetic trees.