Jenny Listman

Data Science Consultant for Small Businesses & Nonprofits


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I can help your nonprofit or small business:

  • Get your data into a useable format and find data that you might not know you have.
  • Analyze, summarize, & visualize your data to provide insight to you or your potential investors, clients, or donors.
  • Tell your story with data.
  • Analyse data through clustering, decision trees, and other machine learning tools.

I have interdisciplinary training:

  • B.A. in Biology, University of Pennsylvania in 1991
  • PhD in Anthropological Genetics, New York University in 2009
  • Postdoc at Yale University School of Medicine, Psychiatric Genetics in 2011

I’m experienced in data wrangling, big data, machine learning, clustering, and data visualization. I’m skilled in communicating complex scientific and statistical concepts or results to colleagues and lay audiences via grants, blogging, project summaries or reports, public talks, and research publications.

I was most recently Assistant Director, Program Development and Evaluation at NYU’s Center for K12 STEM Education where I conducted and published quantitative assessments and outcomes evaluations of K-12 teacher PD and student programs.

Before that, I used genomic data to research human evolutionary and migratory history, a.k.a ancestry genomics. I collected saliva samples as a DNA source from over 500 individuals in rural Thailand to create a DNA resource of six ethnic populations. I also conducted research on the evolutionary history of genes involved in alcohol metabolism and substance abuse.

You can view my resume.

Latest Post

Mar 15, 2018

Scraping The CAWP Site To Make a Shiny App To Search For Women Running For Office

By Jenny Listman An Interactive App To Visualize Women Runnning for State or Federal Offices This project was created with data scraped from the website of the Center for American Women in Politics at Rutgers University. The Center conducts research on women’s participation in politics in America and maintains a list of women who are or potentially will be running for US Congress and State offices. The code scrapes and combines data from their lists of women candidates, cleans and creates new variables, and visualizes the data in an interactive shiny map and searchable data table using plotly and DT packages . ...Read More

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