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NASA Center for Climate Simulation
Data Scientist
June 25, 2026 – Present
spectraclass
November 18, 2020 – August 29, 2023
Jupyterlab workbench supporting visual exploration and classification of high dimensional sensor data.
View Projectfloodmap
July 16, 2020 – October 28, 2022
This project computes surface water extents from lake shapefile boundary maps. It uses the NRT Global Flood Mapping products produced from the LANCE-MODIS data processing system at NASA Goddard to compute the probability of water in each spatial cell within each shapefile boundary map. It then thresholds this probability to produce water mask files.
View Projecthyperclass
April 22, 2020 – December 7, 2020
Methods for hyperspectral image classification developed by the NASA Goddard Innovation Lab
View ProjectcliMLe
June 13, 2018 – December 20, 2018
Machine Learning development for climate applications
View Projectedask
June 12, 2018 – January 9, 2020
Earth data analytics using the Dask / XArray toolkit.
View Projectesgf-compute-api
July 8, 2016 – March 10, 2021
The API for end users for esgf compute stacks (cwt)
View ProjectCDAS2
May 5, 2016 – July 18, 2017
Climate Data Analytic Service provider built on scala, Spark, Akka, Haddop, and python tools such as UVCDAT, etc. Designed to be deployed with the nasa-nccs-cds/CDWPS framework.
View ProjectCultural Fit Analysis
The candidate's projects are heavily concentrated in climate science and earth data analytics, aligning well with roles requiring specialized domain knowledge in these areas. The diversity of technologies used (Python, Scala, Java, JavaScript, Shell, Dockerfile) suggests adaptability and a broad technical interest. The current role at NASA Center for Climate Simulation further reinforces a strong cultural fit for research-oriented or scientific data roles. However, the projects are all personal, which might indicate a preference for individual contribution over team-based work, though this cannot be definitively concluded without further information.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a focus on complex scientific data problems, suggesting strong problem-solving and analytical skills. The nature of the projects (e.g., API development, data analytics toolkits) implies an ability to work on structured, long-term initiatives. However, without specific assessment data, it is difficult to evaluate communication, teamwork, or stress handling directly.