Charles Grady, Developer in Overland Park, KS, United States
Charles is available for hire
Hire Charles

Charles Grady

Verified Expert  in Engineering

Back-end Developer

Overland Park, KS, United States
Toptal Member Since
September 26, 2022

Charles is primarily a back-end developer specializing in Python. He has more than 16 years of experience developing RESTful APIs, high-throughput computations, and cluster interfaces in an open source environment. Charles published papers, gave conference presentations, and taught domestic and international workshops showcasing the tools he created, the community infrastructure, and his research projects.


Cedar Build, Inc
GIS, Python, Spatial Analysis, QGIS, GDAL/OGR, GDAL, Workflow, GitHub, Pytest...
Chegg - Thinkful, Inc.
Python, Flask, Microservices, Agile Sprints, Braze, SQLAlchemy, Alembic...
University of Kansas
Algorithms, API Documentation, API Integration, APIs, Back-end, Big Data...




Preferred Environment

Python, Slack, pylint, Flask, CI/CD Pipelines

The most amazing...

...thing I've developed is a binary matrix randomization algorithm. This algorithm allowed researchers to look at patterns at previously impossible sizes.

Work Experience

Back-end Developer

2023 - 2024
Cedar Build, Inc
  • Created an automated workflow for the client to take raw input data from various sources through pre-processing and analytical tools to combine and derive outputs the client was interested in for public consumption.
  • Developed methods for identifying and classifying edges for land parcel polygons using attribute data and spatial relationships to enable additional processing and derived attribute analyses.
  • Developed a dynamic configuration schema that the client can easily update. Generated multiple examples along with documentation for using and updating the configuration files for multiple municipalities.
  • Created tools for determining which building codes affect specific parcels. This required identifying triggering parcels and then the parcels they affect and following region-specific rules for handling all the building codes for a parcel.
  • Developed workflows and tools designed to be scaled, parallelized, and checkpointed in order to operate on larger and more complex municipalities.
  • Automated testing, builds, packaging, release notes, and code quality control using GitHub actions, pytest, and pre-commit.
Technologies: GIS, Python, Spatial Analysis, QGIS, GDAL/OGR, GDAL, Workflow, GitHub, Pytest, GitHub Actions, Build Releases, Git, Unit Testing, Documentation, Markdown, API Documentation, Python 3, Packaging, Debugging, Data Pipelines, Software Documentation, Back-end Development, CSV, Automation, Data Processing

Python/Flask Developer

2022 - 2023
Chegg - Thinkful, Inc.
  • Migrated an independent product with its own microservices into a larger umbrella product to simplify interactions between products and improve performance.
  • Resolved existing technical debt and migrated and rewrote scripts and tools to fit the client's new project structure to improve performance, leverage new tools, and simplify data access and testing.
  • Migrated the client's existing customer interactions called through Customer.IO APIs to use customer-based and event-based Braze APIs.
  • Updated dev and production Docker containers for updated software products.
  • Participated in code peer reviews as part of the build deployment cycle.
  • Tracked and fixed bugs using Jira as a reporting tool and Agile task planning.
Technologies: Python, Flask, Microservices, Agile Sprints, Braze, SQLAlchemy, Alembic, CI/CD Pipelines, Docker, Docker Hub, Migration, Amazon Web Services (AWS), Zoom, Slack, Stripe, CircleCI, Jira, GitHub, Git, Code Review, Software Integration, Unit Testing, API Development, Debugging, Back-end Development

Senior Research Software Engineer | BiotaPhy Project

2016 - 2022
University of Kansas
  • Developed software for performing mathematical computations at novel data and computational scales.
  • Converted scripts created by non-programmers into production-quality software tools suitable for larger data scales and use in a more general audience.
  • Built, maintained, and moderated a common code repository for collaboration between five institutions. This repository utilized pre-commit and CI/CD pipelines to ensure that code was well-tested and met quality standards.
  • Created and used workflows for big data analyses that were then interpreted by biologists.
  • Co-authored publications in scientific journals describing the research.
  • Designed and implemented algorithms for computing new analyses.
  • Presented research and led workshops at conferences and webinars.
  • Documented software tools and APIs for public and software consumption.
Technologies: Algorithms, API Documentation, API Integration, APIs, Back-end, Big Data, Biology, Authentication, Python, Pytest, Python 3, Cluster, Web Services, REST APIs, REST, Training, Publication, Research, High-performance Computing (HPC), Data Engineering, HTTP, HTTPS, GitHub, GitHub Pages, CI/CD Pipelines, pylint, PyPI, NumPy, Modeling, GIS, QGIS, Testing, Programming, Statistical Methods, Databases, Geographic Information Systems, Spatial Algorithm Design, Slack, Matrix Algebra, Statistics, DendroPy, Parallel Programming, SQL, Microsoft Word, Microsoft Excel, Workshops, Object-oriented Programming (OOP), OpenAPI, Swagger, Multithreading, Tech Conferences, Conference Speaking, Presentations, Lint, Linux, Ubuntu, R, Cluster Computing, Scaling, EML, Documentation, Metadata, Architecture, Software Design, Software Integration, Spatial Analysis, Unit Testing, Open Source, API Development, Debugging, Mathematics, Data Pipelines, Software Documentation, Technical Architecture, Back-end Development, Artificial Intelligence (AI), CSV, Automation, Data Processing

Senior Research Software Engineer

2012 - 2022
University of Kansas
  • Developed an algorithm and implementation method for randomizing binary matrices while maintaining row and column totals for null model creation at multiple orders of magnitude larger scales while requiring a fraction of the time and resources.
  • Built a suite of biodiversity analysis tools for biological researchers designed to be easily extended and for operation on a single machine or a multi-machine computational architecture.
  • Designed and implemented a RESTful web API for accessing biodiversity data and workflow tools in a high-throughput computational environment.
  • Created tools to analyze single-species and communities of species occurrence records to establish each record's information value and novelty across a multi-variate space.
  • Developed high-throughput computational workflows for analyzing billions of museum specimen records by aggregating records from multiple, heterogeneous sources, cleaning that data, and deriving numerous single- and multi-species outputs.
  • Published articles in scientific journals describing tools created for biodiversity research.
Technologies: Python, Python 3, NumPy, APIs, Flask, CherryPy, Solr, PostgreSQL, MySQL, SQLite, Cluster, Supercomputers, Algorithms, Modeling, HTTP Clients, GIS, QGIS, Workflow, Git, GitHub, Testing, Spatial Statistics, Statistical Methods, Apache2, Authentication, Biology, CI/CD Pipelines, Cluster Computing, CSS, Databases, Data Engineering, DendroPy, Docker, Documentation, EML, Big Data, Microsoft Word, Microsoft Excel, Windows, Ubuntu, Linux, Lint, Geographic Information Systems, High-performance Computing (HPC), HTML, Graphs, JavaScript, R, REST, Object-oriented Programming (OOP), pylint, OpenAPI, Swagger, SQL, Workshops, Presentations, Conference Speaking, Tech Conferences, API Integration, API Documentation, REST APIs, Agile Sprints, Gimp, Multithreading, Back-end, Data Structures, JSON, Scripting, HTTP, Programming, Spatial Algorithm Design, Slack, Pytest, Matrix Algebra, Statistics, Parallel Programming, XML, GitHub Pages, HTTPS, Research, Scaling, Web Services, Metadata, Architecture, Software Design, Software Integration, Microservices, Spatial Analysis, Unit Testing, Open Source, API Development, Debugging, Mathematics, Data Pipelines, Software Documentation, Technical Architecture, Back-end Development, CSV, Automation, Data Processing

Software Developer

2007 - 2012
University of Kansas
  • Developed data and processing web services for creating species distribution models for all species with enough data.
  • Designed computational workflows for processing input occurrence records and interfacing with modeling software to create models and distribution projections exploring the impacts of climate change.
  • Presented work and research at various conferences.
  • Created a visual interface representing the computational status of the nodes in a compute cluster so that users can see how various computational jobs move throughout the system.
  • Built a client library for collaborators to use for interfacing with computational services.
Technologies: Python 2, CherryPy, Apache2, PostgreSQL, MySQL, Flash, XML, JSON, Cluster, APIs, REST, REST APIs, Web Services, API Documentation, Algorithms, Modeling, GIS, QGIS, Testing, Programming, Statistical Methods, Databases, Pytest, SQL, Microsoft Word, Microsoft Excel, Workshops, Object-oriented Programming (OOP), HTML, JavaScript, Research, Gimp, API Integration, Tech Conferences, Conference Speaking, Presentations, Linux, Ubuntu, High-performance Computing (HPC), Cluster Computing, Authentication, EML, Documentation, VisTrails, Metadata, Architecture, Software Design, Software Integration, Microservices, Unit Testing, Open Source, API Development, Debugging, Data Pipelines, Software Documentation, Back-end Development, CSV, Automation, Data Processing

Software Developer

2006 - 2007
Specify Collections Consortium (via University of Kansas)
  • Developed a web interface for the Specify collection management software.
  • Created the installer for the collection management software using InstallShield.
  • Provided user support for issues impacting the web interface, installer, and various others, utilizing Bugzilla.
Technologies: Jakarta Server Pages (JSP), InstallShield, Microsoft SQL Server, Apache2, IIS, Apache Tomcat, Bugzilla, Algorithms, Testing, Programming, Databases, SQL, Microsoft Word, Microsoft Excel, Object-oriented Programming (OOP), HTML, JavaScript, XML, Research, Presentations, Linux, Windows, Authentication, Web Services, Documentation, Metadata, Architecture, Software Design, Software Integration, Microservices, API Development, Debugging, Data Pipelines, Back-end Development, CSV, Automation

Biodiversity Research Software for the BiotaPhy Project

Various summaries and explorations of large-scale biodiversity analyses. I collaborated with multiple research biologists to perform, analyze, and summarize large biodiversity analyses to answer questions that previously could not be computed.

I collected and pre-processed raw input data, performed hundreds of thousands of single-species workflows, and generated large-scale multi-species data structures—including hundreds of thousands of species by hundreds of thousands of geographic sites—and some additional generated data structures that were then used to generate global analyses. This required significant data engineering, involving 5+ billion input records, and new data structures and methods for computing global analyses.

The portions of these projects that were possible in the past would have taken several months to years of computational time, but I had reduced the time required to several days. Other portions of the analyses were only possible at smaller scales—hundreds of sites by hundreds of species at most—and I was able to perform them 10,000 times for each analysis in matters of hours at up to 10 to the 12th power in data sizes. I then co-authored manuscripts with the researchers describing the methods.

Biological Collection Comparisons Tool

A suite of tools for analyzing biological collection holdings against all publicly available collection data. I created a package of Python-based tools for analyzing specimen records and where they fit among all published specimen records for each species. This project requires a large amount of data ingestion and data engineering to compare records that are served in various formats and may need updating; for example, taxonomic names can change over time.

The total input data set is approximately 5 billion records from 6 data sources, but it can be expanded as data becomes available. I wrote tools to process these inputs and standardize them so they can be grouped and assessed one species or collection at a time.

Each specimen record undergoes many single- and multi-variate analyses across various dimensions to determine how likely each is to be an outlier, representative, unique, a duplicate, among others. Data is summarized at various taxonomic and phylogenetic levels to assess larger patterns and the collection density and distribution. The end goal is to create actionable items for a collection to improve for funding reviews, public presence, and research value.

Lmpy | Library of Biodiversity Analysis Tools
Lmpy is a library of open source tools used for biodiversity analyses. These tools originated as part of the Lifemapper back end for various high-performance and high-throughput computations and were thought to be potentially valuable for collaborating biologists. The data structures and methods can be used locally, and any extensions developed using these objects and tools can be directly integrated into the Lifemapper computational back end without additional modification.

The motivation behind this project came from the need to modify and reimplement various scripts and software written by biologists that could not scale to their needs. My involvement in this project started from those re-implementations, as I developed the library so that the biologists we collaborated with could use code, tools, and scripts designed with computational performance in mind. I set up the repository, including CI/CD for testing, PyPI packaging, Docker builds, and documentation builds, created new tools, and reimplemented others, including my binary matrix randomization algorithm. I contributed to nearly all of the code and documentation until version 3.1.21.

Parallel Implementation of Dijkstra's Algorithm for Computing Coastal Inundation Height

A parallelized implementation of Dijkstra's algorithm was designed to take advantage of parallelized resources to compute coastal inundation height, flood modeling, or other shortest path computations. The project was written in Python using WorkQueue to compute worker management.

The project splits raster files into manageable-sized chunks to be worked on in parallel. These grid chunks can be of heterogeneous sizes and allow data sizes and scales that would not be feasible without specialized hardware. The critical points of the method are that individual chunks, or tiles, can be operated on in parallel and isolation and that the computations can be repeated as necessary when new information is determined. This results in an algorithm that is not necessarily as work efficient as standard Dijkstra's algorithm but runs in significantly less real time given the ability to utilize parallel resources, including massively parallel resources and supercomputers while requiring a fraction of the memory resources needed. In addition, heterogeneous data scales can be used for regions with higher resolution data.

I designed and implemented this project for my master's thesis and received honors for it.

Lifemapper Client Library

A Python client for accessing the Lifemapper project's various web services, such as OGC, RESTful, and authentication. I created a Python client library, including most of the web services it interacted with, to access the web services our project provided.

This client was aware, as dynamically as possible, of all of the services and data models that were currently exposed and was able to construct workflow requests for the computational back end. The client library was then distributed to our collaborating researchers, the general public, and additional clients, such as a QGIS plugin, that used this library as a liaison for interacting with the Lifemapper web services.

Documented, Re-executable Workflows for VisTrails
A plugin for the VisTrails workflow software. I created this plugin that reads an ecological metadata language file, pulls the input data locations (web or local), and reads the prescriptive process steps to generate the same workflow used to create the original data.

This project allows researchers to include their input data and processes in a standardized format with their publications. Consumers of those publications can then use these data or metadata packages to recreate the researcher's findings and tweak those workflows as desired for different datasets or to perform additional analyses.

I presented this work at the 2011 Environmental Information Management Conference, and a paper covering this work was published in the proceedings.

Web Interface for the Specify 5 Collection Management Software

A web interface add-on for the Java-based Specify 5, a biological collection management software. I wrote the web interface for exposing an institution's biological collections.

The software was written using Java Server Pages and could be installed with Microsoft IIS or Apache. My portion of this project was to expose data from a full-text index of the collection database. This software was distributed and enabled by hundreds of institutions to expose their collections for public consumption. It was also highly configurable and provided interfaces for collection managers to see what data was accessed.

This was an early-career project, and—while I believe there are a couple of installations that are still live—there are many software packages available now that have made this project obsolete.
2009 - 2017

Master's Degree in Geographic Information Science

University of Kansas - Lawrence, Kansas, USA

2001 - 2006

Bachelor's Degree in Computer Science

University of Kansas - Lawrence, Kansas, USA


Machine Learning A-Z: AI, Python & R + ChatGPT Prize [2024]



The Complete JavaScript Course 2023: From Zero to Expert!



Data Science

University of New Mexico


NumPy, REST APIs, API Development, DendroPy, OpenAPI, Pandas, SQLAlchemy, Stripe, GDAL/OGR, GDAL


GIS, Solr, Cluster, Git, GitHub, pylint, Pytest, PyPI, Microsoft Word, Microsoft Excel, GitHub Pages, Slack, Flash, InstallShield, Apache Tomcat, Bugzilla, Braze, CircleCI, Docker Hub, Zoom, Jira


Python, Python 3, SQL, R, XML, C++, HTML, JavaScript, Python 2, Java, CSS, JavaScript 6, Markdown


Testing, Object-oriented Programming (OOP), REST, Unit Testing, Data Science, Parallel Programming, High-performance Computing (HPC), Microservices, Automation


Data Pipelines, PostgreSQL, Databases, JSON, MySQL, SQLite, Microsoft SQL Server


Docker, Apache2, Windows, Ubuntu, Linux, Amazon Web Services (AWS)


Flask, CherryPy, Swagger, Jakarta Server Pages (JSP), Alembic


APIs, Algorithms, Workflow, Programming, Spatial Algorithm Design, Metadata, Documentation, Web Services, API Integration, API Documentation, Back-end, Data Structures, Scripting, Research, Architecture, Software Design, Software Integration, Debugging, Software Documentation, Back-end Development, CSV, Data Processing, Modeling, HTTP Clients, Spatial Statistics, Statistical Methods, Geographic Information Systems, CI/CD Pipelines, Matrix Algebra, Statistics, Workshops, Data Engineering, Big Data, EML, Authentication, Scaling, Cluster Computing, Maps, Training, Lint, Presentations, Conference Speaking, Tech Conferences, Agile Sprints, Multithreading, HTTP, Spatial Analysis, Open Source, Technical Architecture, Supercomputers, QGIS, Operating Systems, Cartography, Publication, VisTrails, Biology, Graphs, Gimp, HTTPS, IIS, Migration, Code Review, GitHub Actions, Build Releases, Packaging, Mathematics, Machine Learning, Decision Trees, K-means Clustering, Random Forests, Artificial Intelligence (AI), Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN)

Collaboration That Works

How to Work with Toptal

Toptal matches you directly with global industry experts from our network in hours—not weeks or months.


Share your needs

Discuss your requirements and refine your scope in a call with a Toptal domain expert.

Choose your talent

Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.

Start your risk-free talent trial

Work with your chosen talent on a trial basis for up to two weeks. Pay only if you decide to hire them.

Top talent is in high demand.

Start hiring