Mark Harbison

mark.f.harbison@gmail.com   |   www.harbison.one

916-475-9461

www.github.com/mfh92   |   linkedin.com/in/mr-mark-harbison

Objective:

Mark is seeking a data analyst position where he can leverage his 25+ years of experience working in math and statistics education. He communicates difficult data concepts with intuitive storytelling and precisely tailors his message across different audiences.

Relevant Projects:

Discography Web-Scraping

    • Language: Python
    • Libraries: requests, BeautifulSoup, langdetect
    • Crawls Wikipedia pages of musical artists and bands and stores their album names.
    • Over 29,000 records stored using the scraper.


Conference Attendance Trends

    • Languages: R, JavaScript
    • Libraries: ShinyApps, rgeos, dplyr, leaflet
    • Summarizes the attendance and community college affiliation for an annual conference hosted by the California Mathematics Council of Community Colleges (CMC3).
    • Results were used by the executive board to increase attendance from under-represented institutions.


Recreational Mathematics Article Lookup

    • Languages: PHP, SQL
    • Indexes 2,600 records from 1,600 articles published to the Journal of Recreational Mathematics that were previously only listed in print.


Invited Presenter

    • Mathematical research with marcros to find Pythagorean Triples.
    • Statistics presentation on Goodness-of-Fit hypothesis tests.

Experience:

Content Expert, XYZ Homework, from 2021 to the present

    • Programmed over 4000 algorithmic homework questions per year in Statistics, Calculus, and Algebra


Professor of Statistics and Mathematics, Sacramento City College, from 2002 to 2018

    • Taught courses in Introduction to Probability and Statistics, Algebra, Calculus.
    • Analyzed data, wrote curriculum, taught innovative lessons, evaluated abilities, reported progress, mentored students, participated on multiple committees at once.
    • Created and ran an innovative second chance, six-day program for students with marginal final course grades; 95% of statistics students achieved a passing grade through the program.

Education:

M. A., Mathematics

    • including coursework in Advanced Stochastic Statistics
    • San Diego State University


LinkedIn Certificates

    • IBM Python 101
    • Integrating Tableu and R
    • R Statistics Essentials
    • Master R for Data Science
    • Logistic Regression in R
    • R for Excel