Rowan is available for hire
Hire RowanRowan Copley
Verified Expert in Engineering
Data Science Developer
Location
Portland, United States
Toptal Member Since
September 9, 2019
Rowan has nine years of industry experience building systems and models that make technical, complex data easier to understand. He has built maps of the human genome, NSF-funded serious games, and various dashboards, APIs, data pipelines, and apps. Rowan has collaborated with scientists, journalists, artists, and other engineers. He's friendly, communicative, and comfortable advocating as a technologist as well as a project manager.
Portfolio
Freelance
Microsoft Excel, Jupyter, Pandas, Python, Data Science
Stanford Department of Medicine, HealthRex
Google BigQuery, ETL, Python, Machine Learning, Data Science
Thespie
Amazon Web Services (AWS), PostgreSQL, Pandas, Django, React, Python
Experience
Availability
Part-time
Preferred Environment
Python, Pandas, Jupyter Notebook
The most amazing...
...project I've built from scratch is an interactive map of the complete human metabolome that visualized experimental data.
Work Experience
Data Science Consultant
2020 - PRESENT
Freelance
- Collaborated with an investigative journalist on an article on immigration published in FiveThirtyEight.
- Served as a judge in data.org's Inclusive Growth and Recovery Challenge, a competition to spur data science for social impact with $10 million in prize money.
- Collated public government data into a single cohesive dataset to estimate Covid-19's effect on the November elections.
- Explored automating data collection on Chinese censorship for the art project Firewall Cafe.
Technologies: Microsoft Excel, Jupyter, Pandas, Python, Data Science
Data Science Consultant
2020 - 2021
Stanford Department of Medicine, HealthRex
- Developed and implemented strategy for integration with partner org's inference model.
- Implemented an ETL pipeline for multi-party computing using health data.
- Documented best practices, including publishing a Python package.
- Performed training and got certified by CITI and Stanford's HIPAA training to work with protected patient data.
Technologies: Google BigQuery, ETL, Python, Machine Learning, Data Science
Back-end Lead
2019 - 2021
Thespie
- Designed and built a content recommendation engine for theater-related streaming content.
- Cut major Django API call times by ~80%. Built profile, news, search, and user list pages.
- Designed and built a system for storing user data.
- Wrote feasibility studies on TV apps, paywall integration, and user rating prediction.
Technologies: Amazon Web Services (AWS), PostgreSQL, Pandas, Django, React, Python
Software Engineer
2019 - 2019
FinOptimal (freelance)
- Built an OAuth2 integration module for connecting the codebase with the Quickbooks API.
- Automated the payroll journal entry creation for several of FinOptimal's clients.
- Ported tens of thousands of lines of code into Python 3.
Technologies: Intuit QuickBooks, Pandas, Python
Front-end Engineer
2018 - 2018
Nimbus IoT (freelance)
- Delivered a dashboard for visualizing contaminants in water and air from a network of sensors built on Angular, Node, and D3.
- Built a data store to centralize front-end data handling, improving code modularity and speed.
- Collaborated with back-end developers to ensure that data sent to the front-end was well-structured and compact.
- Prototyped new charts with Nimbus based on client feedback.
- Discovered and pin-pointed the source of an in-browser memory leak using Python for data analysis.
- Prototyped and built timeline, multi-bar, and custom pollutants chart with D3 and CSS.
- Advised on the best way of representing data for user understanding.
Technologies: JavaScript, Angular, D3.js
Software Engineering Consultant
2018 - 2018
Rheos Medicines (consulting)
- Built a dashboard from the ground up for use by Rheos scientists to explore the effects of disease on the human metabolome, working with the client from design to delivery.
- Developed the ability to switch between multiple dataset renderings, visualising the effects of different substances on the metabolome.
- Built the front end with D3.js, Node, Express, and Google Maps API that renders in less than a second.
- Built a pipeline with Python and Pandas which renders tiles for over 40,000 objects at seven zoom scales, taking in an Excel file and outputting image tiles for the front end.
- Created a search and URL integration for specifying a particular metabolite and dataset.
- Built a search functionality using jQuery to quickly find any node in the graph.
- Modularized the rendering pipeline so that any future dataset could be easily rendered.
Technologies: D3.js, Node.js, JavaScript, Google Maps, Python
Software Engineer
2017 - 2018
NuMedii (freelance)
- Developed a graph-based dashboard for scientists to see results of NuMedii's proprietary enrichment algorithm and explore the relationship between drugs, genes, and diseases.
- Co-authored a paper on drug discovery in rare and complex diseases.
- Worked with CSO and CTO to develop the right interface for expanding disease signatures and drug enrichments.
- Streamlined code for building and simulating the graph using D3.js, a 10x speed improvement.
- Integrated MongoDB with a proxy for serving data to the front end.
Technologies: jQuery, MongoDB, Express.js, D3.js, JavaScript
Software Engineer
2016 - 2017
GoChip (contract)
- Developed major features for React Native and React + Electron desktop apps.
- Built a user-facing update and caching process for the desktop app.
- Collected and analysed data with Python to help the development team make technical decisions.
- Wrote a proxy server with Node.js for cryptographic keys that improved load times of our app several-fold.
- Built and tested RESTful architecture for user administration.
Technologies: JavaScript, Electron, React Native, React
Data Science Mentor
2015 - 2016
Thinkful (freelance)
- Assisted data science students to understand concepts and successfully graduate from the course.
- Contributed updates to course materials, improving clarity.
- Guided students through understanding of KMeans, kNN, SVM, and other ML topics.
- Produced my own models using datasets of bike rentals, weather, GDP, and loans using the Python data science stack and MySQL.
- Provided feedback and advice on students' keystone project, using a topic and dataset of their choice.
Technologies: Scikit-learn, Natural Language Processing (NLP), GPT, Generative Pre-trained Transformers (GPT), Pandas, Python
Research Engineer
2012 - 2015
Center for Game Science, University of Washington
- Co-developed the synthetic biology research game Nanocrafter.
- Spearheaded a social scoring model for the game (recognized in an award).
- Demonstrated our lab's work at DARPA Demo Days 2014 at the Pentagon.
- Rebuilt the game physics engine to be based on Box2D.
- Assisted Synthetic Biology researchers in their learning ramp-up for new players.
Technologies: Python
Experience
ReconMap
Tests on the human metabolome create enormous amounts of data, and if you want to be able to understand and explore that data intuitively, you need to make visualizations with it. Rheos Rx approached me to design and build a version of ReconMap, which they could use to visualize information from tests they were performing.
The metabolome was represented as a massive, static graph layout with over 20,000 nodes, and more than 20,000 edges. I did a number of tests to see how to best display this information quickly at many zoom levels and came to the conclusion that the best way was to use the Google Maps JavaScript API. Everything I built for the project centered around that: A pipeline in Python to color nodes and edges based on a dataset of experimental results, rasterize the vector image, and slice it into tiles. A JavaScript front end used the Google Maps API to serve the images, as well as search for specific reactions or metabolites.
The metabolome was represented as a massive, static graph layout with over 20,000 nodes, and more than 20,000 edges. I did a number of tests to see how to best display this information quickly at many zoom levels and came to the conclusion that the best way was to use the Google Maps JavaScript API. Everything I built for the project centered around that: A pipeline in Python to color nodes and edges based on a dataset of experimental results, rasterize the vector image, and slice it into tiles. A JavaScript front end used the Google Maps API to serve the images, as well as search for specific reactions or metabolites.
Evergreens of Washington
https://dovinmu.github.io/cascadia-maps/washington.htmlAn interactive map of Washington state for exploring which trees are native to which ecoregions, and the extent of those trees' region.
Python Viz Notebooks
https://github.com/dovinmu/python-viz-notebooksA GitHub repository for comparing Python libraries for data visualization, exploring what's possible, and discussing their strengths and weaknesses.
Skills
Languages
Python, JavaScript, Julia
Frameworks
Django, Electron, Angular, Express.js, Flask, React Native
Tools
Git, Jupyter, Microsoft Excel, Microsoft Power BI
Libraries/APIs
React, D3.js, Google Maps, Pandas, Node.js, Scikit-learn, jQuery, Fast.ai, WebGL, Three.js, Dask
Paradigms
ETL, Data Science
Platforms
Jupyter Notebook, Amazon Web Services (AWS)
Other
Natural Language Processing (NLP), Simulations, Machine Learning, GPT, Generative Pre-trained Transformers (GPT), Dashboards, Intuit QuickBooks, Google BigQuery, Maps
Storage
MongoDB, PostgreSQL
Industry Expertise
Accounting
Education
2018 - 2019
Educational Retreat in Neural Networks and Geographic Visualization
Recurse Center - Brooklyn, New York, USA
2007 - 2012
Bachelor's Degree in Computer Science and Mathematics
St. Mary's College of Maryland - Maryland, USA
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