If you are an ambitious high school student interested in pursuing a career in data science, you should look into data science internships before applying to college. An internship demonstrates your eagerness to study and connect with the topic outside of the classroom! In this article, we've put together a thorough list of data science internships for high school students.
The NASA Office of STEM Engagements offers NASA internships at all of its facilities around the United States. If you live close to a NASA site, you can apply for an internship at a nearby research facility. However, if you do not live near one, NASA now offers virtual internships! You may search their database for options available to high school students.
If you're interested in data science, we recommend the Antarctic Study with Satellite Observations internship, which uses machine learning and big data analysis to investigate the properties of Antarctic clouds and their interactions with the surface using long-term NASA satellite observations!
Fee: No fee; stipend is supplied.
Location varies and is unique to each internship given.
The application deadline varies for each internship.
Program Dates: Vary by internship, but should be in one of the following three cohorts:
Autumn is from late August/early September to mid-December (16 weeks).
Spring is from mid-January until early May (16 weeks).
Summer – from late May or early June to August (10 weeks)
High School Students
Must be a US citizen.
Have a minimum of 3.0 GPA.
NIST's Summer High School Internship program is intended for students who have finished their junior or senior year of high school (by the program's commencement date) and are interested in scientific research. This program allows you to engage in cutting-edge research at NIST and work directly with NIST staff scientists and engineers on a specific research topic.
Cost: No participation fee (students must bear lodging and transportation costs).
Location varies from lab to lab.
Application Deadline: February 13, 2024.
Program Dates: June 18, 2024, to August 9, 2024 (tentative, depending on prior years' dates).
Ladder Internship is a selected program that allows high school students to collaborate with start-ups on data science-related projects. The program is led by Harvard graduates, and you may collaborate with startups from places like YCombinator and Stanford. Ladder Startups operate in a variety of disciplines, including machine learning and artificial intelligence, finance, technology, environmental science and sustainability, healthcare and medical, business and marketing, media and journalism, and more.
Cost: US$1990
Location: Remote
Application Deadlines: June, September, December, and February (4 cohorts per year). The upcoming application deadline is January 14, 2024.
Eligibility: Students can work 10-20 hours each week for 8-12 weeks. Open to high school, undergraduate, and gap year students.
The University of Chicago's DSI Summer Lab is a compensated 10-week summer research program for high school and college students focused on applied, multidisciplinary data science research. In this program, you will be partnered with a data science mentor from a variety of fields, including data science, climate and energy policy, computer science, and more! Your research mentor will help you improve your abilities in research techniques, procedures, and teamwork. You will get a grasp of core data science approaches and receive specialized training in the application fields. The program concludes with a presentation of your final movies – a video you developed that summarizes your research results over the summer. These films will be presented in a professional conference format, allowing you to communicate with your colleagues and ask questions about their work, and vice versa.
Cost: There is no cost; a stipend is offered (US$4,800).
Location: University of Chicago Campus, Illinois.
Application Deadline: January 16, 2024.
Program dates: June 10–August 5, 2024.
Open to all high school students.
It is preferable to have experience with at least one programming language as well as appropriate education (for example, statistics, computer science, and algebra).
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