Data Science Intern

As a Data Science Intern at Boom, your primary responsibilities include developing tools and methods for data acquisition related to our engine development program. You will engage with real-time telemetry and data visualization, conduct data wrangling, and perform post-test data analyses. Additionally, you will have the chance to gain hands-on experience at test sites, contributing significantly to our mission of creating supersonic aircraft.

To qualify for the Data Science Intern role at Boom, candidates should be one year away from graduating in data science, engineering, mathematics, computer science, or a related field. Proficiency in programming languages such as Python, JavaScript, or Go, along with a strong grasp of numerical computing or statistics, is essential. Previous internship or project experience in high-tech industries, especially aerospace, will give you a competitive edge.

The Data Science Internship at Boom is set to run from early June to mid-August, with flexibility to accommodate academic schedules. This position is required to be 100% onsite at Boom's headquarters in Centennial, Colorado, ensuring that interns immerse themselves fully in our innovative environment.

Candidates who have coursework or experience dealing with empirical experimental data, especially in statistical analysis or data visualization, will stand out when applying for the Data Science Intern role at Boom. Experience applying data science techniques, such as modeling, simulation, or data analysis in aerospace contexts, is highly valued and positions you as a strong contender.

While prior internship experience is not strictly mandatory for the Data Science Intern position at Boom, it is strongly preferred. Hands-on project experience in aerospace or related high-tech fields can significantly enhance your application and demonstrate your readiness to tackle the challenges you'll face during the internship.

In your response, highlight specific data visualization tools you've used, such as Tableau or Matplotlib, and discuss a project where these tools played a crucial role. Explain how you translated complex data sets into accessible visuals to support decision-making or insights.

Elaborate on your systematic approach to tackling data analysis problems. Discuss how you identify the problem, gather relevant data, clean and prepare the data, analyze it, and interpret the results, making sure to mention any specific examples where your methodology led to successful outcomes.

Discuss your proficiency in programming languages such as Python, JavaScript, or MATLAB. Provide specific examples of projects where you utilized these languages to solve problems or create tools, and explain the impact of your contributions.

Share a detailed narrative about a team project, focusing on your role, responsibilities, and the impact you had. Highlight how you collaborated with others and any challenges you overcame, showcasing teamwork and communication skills.

Talk about the techniques you utilize to maintain data quality, such as validation checks, data cleaning processes, and regular audits. Provide examples of how these measures have safeguarded the integrity of your analyses.

Discuss any coursework, projects, or relevant internships that have given you insights into the aerospace industry. Emphasize how this background prepares you for the Data Science Intern position at Boom.

Provide a concrete example where statistical analysis played a key role in your project. Discuss the techniques you applied, the challenges faced, and the outcomes resulting from the analysis.

Show your knowledge about Boom, mentioning aspects of the company’s history, innovations, and their commitment to providing sustainable supersonic air travel. Articulate how your values align with their mission.

Outline the resources you utilize, such as online courses, journals, or conferences in the fields of data science and aerospace engineering. Mention specific instances of how you've integrated new knowledge into your work.

Discuss the various techniques and tools you employ for data wrangling, such as Pandas in Python or SQL queries. Provide examples that demonstrate your experience in transforming raw data into a usable format.