James Simkins

Hi there! I'm James, a passionate Data Engineer/Scientist currently working at Synoptic Data PBC. With a strong background in data engineering and software development, I specialize in data ingest within the Synoptic framework. My focus is on assimilating new datasets into the Synoptic database, ensuring efficient and low-latency availability for database queries. Additionally, I love building serverless data pipelines in the AWS cloud environment, establishing relationships with data providers, and disseminating incoming datasets.

On a personal level, I'm fascinated by the fusion of data engineering/science skills with geospatial, meteorological, oceanographic, and earth systems applications. I'm driven to enhance data pipelines, data science techniques, and data applications for organizations whose missions align with my own values. Beyond my work at Synoptic Data, you can find me developing open-source coding packages, running ocean-climate models, forecasting local weather, playing soccer, and playing golf. I'm also the proud owner of Steepwell Tea Company, an environmentally friendly tea business.

Before joining Synoptic Data, I worked as a software developer at the Geophysical Fluid Dynamics Laboratory through Rutgers University. There, I focused on developing code for the Modular Ocean Model 6 ocean model and running multi-decadal ocean-climate simulations. I leveraged various geospatial software products to support these endeavors. Additionally, I developed Python code for data analysis on the model output and created compelling visualizations using the data.

Prior to that, I served as a Data Engineer/Adjunct Professor at the University of Delaware. In this role, I managed the Satellite Receiving Station, created real-time data visualization products, developed meteorological, climatological, and oceanographic algorithms, and taught geospatial programming courses. One of my notable achievements was implementing empirical orthogonal functions to fill gaps in spotty satellite data. I also designed and taught courses on Machine Learning Techniques, Python for Environmental Science, and R for Geospatial Sciences.

I hold a Masters's degree in Atmospheric and Oceanic Sciences from the University of Wisconsin, where I worked as a Research Assistant for the Predictive Ecosystem Analyzer Project (PEcAn). In this role, I regularly contributed software to the modeling framework, implemented linear regression techniques for temporal downscaling of forcing data, and created tools for reproducible ecosystem modeling and forecasting. I completed my degree in 2017.

During my undergraduate years, I actively participated in four federally funded research projects starting from 2013. I graduated with a degree in Meteorology and a minor in Physics from Millersville University. Under the guidance of Dr. Richard Clark, I engaged in three meteorology field experiments. It was during this time that my passion for atmospheric and oceanic sciences truly flourished. I proudly graduated from Millersville in May 2015.

Thank you for visiting my website! Feel free to explore further to learn more about my projects, research, and interests. If you have any questions or would like to connect, please don't hesitate to reach out.

Email: jamessimkins5 at gmail dot com

Github: https://github.com/jsimkins2