Jennifer Shin is a data scientist, product director, and entrepreneur. We met at the AMNH Hack the Solar System event, where she (and teammate Adam Ibrahim) tackled the hardest data challenge: generating DEM (Digital Elevation Model) files for the surface of Venus. Between the inherent challenge of seeing the surface of a planet when clouds that obscure most of the view, and the very old and strange file format of the NASA Ames Stereo Pipeline, it was a very daunting task. Nevertheless, they persisted, and produced notes about their approach for future data integrators to build from.
After the hackathon ended, we discussed our past experiences with making data actionable through data cleaning, visualization, and statistics. I felt she has had unique journey towards becoming a successful data scientist, and wanted to assemble a list of her public work for myself and others to learn from. She was kind enough to share several links from her recent publications and presentations.
Papers
Talks
- [IBM]: Data Science Expert Interview
- [MongoDB]: How to Avoid Common Data Visualization Pitfalls
- [Domino Data Labs]: Fuzzy Data Matching to the Rescue
- [Databricks]: Fuzzy Matching on Apache Spark
Statistics
- [Strata Data Conference NY 2018]: Assumptions, Constraints, and Risks: How the wrong assumptions can jeopardize any model
- [Geckoboard Data Literacy Series]: A Guide to Basic Data Analysis
- [CUNY]: Webinar: The Role of Statistics in Data Science
Data Visualization Articles
Select Interviews / Panels / Talks
- [IBM Big Data Hub]: Big Data Analytics Hero Interview and Comic
- [Forbes]: Data Science as a Service is Almost Here, Making it Even More Important to Understand Data
- [Forbes]: Keep your AI Algorithms Accurate and Adaptable
- [Republic of Korea]: 8th International Workshop on Innovative Statistical Methods
You will find updates on Jennifer’s work on Twitter at @jennjshin, or through one of her graduate courses at NYU.