Cornelis Jan Drost, Developer in Auckland, New Zealand
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Cornelis Jan Drost

Verified Expert  in Engineering

Software Developer

Auckland, New Zealand
Toptal Member Since
March 7, 2022

Cornelis is a developer, mathematical modeler, and researcher with experience working in tech at Amazon and Biomatters, and startups at and Ubiquetherm. He thrives on solving new and complex problems, learning new skills and background knowledge, and excels at communicating requirements and results. Cornelis has experience in software development and supporting skills, such as data analysis, visualization, math, simulation, and complex systems.


Python, Physics, Ray Tracing, Simulations, Data Visualization, Data Analysis...
Java, Molecular Biology, Computational Biology, Research, ETL, Pandas...
Python, APIs, SDKs, Cryptocurrency, Cryptography, Research, JavaScript...




Preferred Environment

PyCharm, Ubuntu, Windows, Slack, Discord, Amazon Web Services (AWS)

The most amazing...

...thing I've worked on is Thrive, an open-source evolution game that has inspired thousands to learn more about biology and evolution.

Work Experience

Research Engineer

2021 - PRESENT
  • Developed a data pipeline for validating, analyzing, and managing results from multiple physics simulation systems. Used those results in downstream simulations.
  • Automated a time-consuming manual process that took two to three days of founder's time over two weeks to a pipeline that could be launched in under five minutes and completed in under a week.
  • Refactored, replaced, and updated error-ridden "works-once" code with reusable, scalable, and reliable software.
  • Converted an impossible-to-verify process, which left the company without the confidence to proceed based on its output, into one with provably correct output and well-understood assumptions and limitations.
  • Introduced, set up, managed, and advised on the use of source control, software project management, and quality control.
  • Mentored junior developers and applied scientists with programming roles.
Technologies: Python, Physics, Ray Tracing, Simulations, Data Visualization, Data Analysis, Mentorship, Data Pipelines, Data Engineering, Data Validation, Physics Simulations, Jira, Agile Project Management, Complex Problem Solving, Research, Amazon Web Services (AWS), ETL, Pandas, Software Development Lifecycle (SDLC)

Senior Java Developer

2020 - 2021
  • Developed, maintained, and supported features for the world-leading bioinformatics package Geneious Prime.
  • Participated in peer-code review, regularly being commended on going the extra mile to understand a feature in the context of the complex system it was adding to and uncovering obscure bugs and failures.
  • Responded to bug reports over e-mail. Investigated, triaged, and fixed bugs as appropriate.
Technologies: Java, Molecular Biology, Computational Biology, Research, ETL, Pandas, Software Development Lifecycle (SDLC)

Python | Research Developer

2019 - 2019
  • Developed and maintained the client-side API for interacting with the Fetch cryptocurrency ledger.
  • Developed and maintained an SDK for creating smart contracts to run on the Fetch blockchain.
  • Created a lexer and parser for smart contracts, providing correctness feedback and extracting configuration details affecting how a contract could be deployed.
Technologies: Python, APIs, SDKs, Cryptocurrency, Cryptography, Research, JavaScript, REST APIs, Pandas, Software Development Lifecycle (SDLC)

Software Development Engineer

2018 - 2019
Amazon Prime Air
  • Supported the growth of a team of computer vision data analysts from 30 to 180 in six months, providing both software support and developing tools to increase efficiency and scalability.
  • Built robust, minimally visible toolchains to automate data retrieving for analysis, reporting results, and submitting output to a central server.
  • Reduced analyst downtime due to software and human errors by over 90%. Reduced rejection of submitted data by downstream computer vision teams by over 75%.
  • Reduced management burden on group leaders, allowing them to effectively manage five times more analysts.
  • Automated all technical aspects of workflow, significantly simplifying the onboarding of new users and cutting the time per task by about 25%.
  • Added input validation to all user output and automatically retrieved metadata from other sources where possible, reducing the risk of human error.
  • Built additional tools and GUIs to support the peer quality control (QC) of output and standardize the format of quality control feedback to enable tracking and testing of performance improvements.
  • Designed and built a system for the automated creation, prioritization, assignment, and tracking of analyst tasks, eliminating the need for managers to individually assign tasks and enabling senior managers to prioritize work at a broad scale.
Technologies: Python, Bash, Amazon DynamoDB, AWS Lambda, APIs, Data Engineering, Data Visualization, Graphical User Interface (GUI), Git, Data Management, Complex Problem Solving, Data Pipelines, REST, Amazon Web Services (AWS), REST APIs, ETL, Pandas, Software Development Lifecycle (SDLC)

Task Management System for Data Analysts

This is a local scripted workflow and AWS-hosted management system for the assignment, prioritization, and tracking of data analysis tasks to be completed by a team of over 150 analysts.

Tasks spanned a multi-step workflow, such that the completion of one task could trigger the queueing of multiple dependant tasks or that the failure of a QC step could cause a task to be repeated. A key feature of the system was prioritization, allowing managers to set priority rules based on task age, type, and metadata retrieved from other sources. The ability to do this at a high level saved over 50 hours a week across six managers compared to the previous manual workflow. The local workflow streamlined or automated away almost all manual data management, eliminating most opportunities for human error and allowing analysts to progress cleanly between tasks.

I designed, developed, and supported the local workflow component of this system, which was in successful use for over eight months while the online component was developed. I also designed, developed, and launched the online component while overseeing the analyst team's day-to-day support and feature requests.

Etch Smart Contract SDK
This Python software development kit (SDK) supports the development of smart contract code in the Etch language for the blockchain.

My primary contribution was the development of a lexer and parser extension for the Etch language. This allowed basic syntax checking before a contract was submitted and allowed the extraction of configuration details from the code. For example, Etch contracts could declare global variables, which would persist on the blockchain, either across all shards (i.e., parallel executions of the chain) or a subset. Correct deployment of contracts containing globals required matching the shards used by the code to those to be deployed to.

I also oversaw keeping the SDK up to date with the rapidly developing ledger API.
2009 - 2013

PhD in Theoretical Ecology

Aberystwyth University - Aberystwyth, United Kingdom

2006 - 2009

Bachelor's Degree in Marine Biology

Aberystwyth University - Aberystwyth, United Kingdom


Pandas, REST APIs


MATLAB, PyCharm, Slack, Jira, Git, GIS, Boto 3


Python, C#.NET, Java, Bash, JavaScript


ETL, REST, Agile Project Management


Windows, Amazon Web Services (AWS), Ubuntu, AWS Lambda


Data Pipelines, Data Validation, Amazon DynamoDB, Amazon S3 (AWS S3)


Mathematical Modeling, Simulations, Analysis, Data Visualization, Biology, Research, Data Analysis, Complex Problem Solving, 3D Math, Statistics, Writing & Editing, Mentorship, Data Engineering, Computational Biology, APIs, Data Management, Software Development Lifecycle (SDLC), Discord, Physics, Ray Tracing, Physics Simulations, Molecular Biology, SDKs, Cryptocurrency, Cryptography, Graphical User Interface (GUI), Amazon API Gateway, Document Parsing, Source Code Lexing

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