Data visualization engineer

Part-time/contract, remote

About Science for America

Science for American (SfA) is a solutions incubator to address urgent challenges in Climate and Energy, Health, and STEM Equity and Education. As a solutions incubator, we define critical problems, identify game-changing solutions, and work to launch and incubate solutions.

As part of our work on STEM Equity and Education, we are developing an interactive data visualization platform to illuminate trends and patterns in STEM education across the United States, leveraging comprehensive data from the Department of Education.

Role Summary

We are seeking an experienced Data Visualization Engineer to refine and enhance a public data visualization tool designed to explore representation within STEM. This position offers the opportunity to collaborate closely with SfA’s STEM Scientist, engaging deeply with a meaningful project and applying your technical expertise to foster greater understanding and drive impactful decisions in STEM education.

We are currently seeking a data visualization engineer to support Phase 1 of our project on a contract basis, with the possibility to extend to Phase 2.

Key Responsibilities

Phase 1: Expand existing prototype
● Refactor existing scripts and Python package to enable reproducible analysis of our dataset and support for others doing similar analyses.
● Enhance and implement data visualization and UI features in our existing prototype visualization written in a Dash framework (Python, Plotly, Dash).
● Scale existing codebase to effectively manage the entirety of our dataset, which includes thousands of universities, 15 years, hundreds of academic disciplines, and multiple demographic groups.
● Brainstorm and implement data visualization and UI approaches to scale our existing visualization, which currently includes one year of data for a subset of disciplines, to include the entirety of our dataset.
● Collaborate on architectural, design, and strategic decisions, contributing to the evolution of the visualization prototype.

Phase 2: Productionize
● Partner with our team to evaluate and select technologies for a scalable and public-facing data visualization tool.
● Transition the prototype into a fully operational and accessible online resource.

● Proven mastery of Python, with specific expertise in libraries such as pandas, numpy, and matplotlib.
● Proficiency in at least one Python-based interactive visualization library (e.g., Plotly, Altair, Bokeh).
● Demonstrated experience in developing data visualizations and front-end/UI solutions, preferably with Dash/Plotly.
● Strong understanding of Python packaging, version control systems (Git), and Linux/bash scripting.
● Experience in deploying data visualizations on web platforms (e.g., Render).
● Independent work style, coupled with the ability to contribute to collaborative decision-making.

Nice to have
● Background working with education datasets (e.g. IPEDS).
● Awareness and understanding of diversity, equity, and inclusion principles, especially as they relate to data handling, analysis, and visualization.
● Expertise in creating accessible data visualizations.
● Experience with other programming languages and frameworks (e.g. Javascript, D3)
● Proficiency managing, analyzing, and visualizing large datasets (e.g. Dask)

Role specifications
● This is a part-time, remote position.
● US-based candidates only. No geographic requirements, but candidates must be able to overlap with working hours in the US Eastern Time Zone.
● We expect that this work will require approximately 10 hours per week over the course of 2-3 months, with the possibility of extension. The exact work plan and duration are flexible and can be mutually agreed upon.

How to Apply
Submit your application here: , including your resume and portfolio examples of 1-2 previous data visualization projects and their underlying code (preferably Python-based). If you have any questions or trouble with the application, please email .

SfA is committed to fostering a diverse and inclusive workplace. We strongly encourage candidates from varied backgrounds and perspectives to apply.