Strong Data Science Scholarship
Learn about our scholarship for students looking to make an impact with data science.
Strong Analytics, a data science consulting and machine learning development firm, is offering a $1,000 (USD) scholarship to secondary and post-secondary students interested in pursuing a career in data science.
At Strong Analytics, we believe that data science empowers us to make positive change across many domains, from health, to education, politics, energy, and more.
Our goal with this scholarship is to encourage motivated students to engage with data science projects and learn the tools and techniques to enable them to make positive impact through data. These projects can be on any topic, though they must use publicly-available, open-access data.
Rules & Eligibility
- The project must use publicly-available, open-access data.
- All analyses, visualizations, and reports must be original.
- Students can work individually or as teams.
- Each student or team may only make a single submission.
- All submissions must include the source code and data necessary to reproduce the analysis.
- Submissions must be hosted at a public repository, such as GitHub.
- All applicants must be currently registered as students at a college/university in the United States or Canada.
How to Apply
- Find a publicly-available dataset.
- Choose an interesting research question in the public interest that can be addressed using these data.
- Using the programming language(s) of your choice (e.g., R, Python), analyze, visualize, and interpret the data.
- Code your analysis such that we can re-run it ourselves to reproduce your results and visualizations.
- Create a presentation (up to 20 slides) that clearly outlines your research question, methods, and findings.
- Submit your presentation as a PDF and a link to your project's reproducible source code repository to email@example.com by the deadline above.
Projects will be assigned an overall score by all three partners at Strong based on the following criteria:
- Creativity: Is the question interesting? Is the approach novel?
- Rigor: Are the methods used appropriate for the problem? Did the author come up with a error-free, thoughtful solution?
- Clarity: Are the questions, methods, and findings clearly communicated? Is the source code readable?
- Reproducibility: Can we reproduce your solution using the data and code provided?
We will consider the current level of education of the student in assessing each of these criteria.
Strong Analytics will not share the names or contact information of applicants with any third-parties without explicit, written permission from the applicants. Award winners may choose to opt-out from having their work published on our website. The award will be paid directly to the student, to be used for their education in the manner of their choosing.
For more information please click "Further Official Information" below.