Zipline is looking to solve the world's most urgent and complex access challenges by building the first instant logistics system that serves all humans equally. The Software Integration team plays a critical role in making sure the software that flies their aircraft works reliably and safely in the real world. The Data Science Intern will apply technical and engineering skills to support hardware systems integration and engineering projects by analyzing large datasets and creating actionable insights.
Requirements
- Familiarity with Python for scientific programming (libraries such as NumPy, Pandas, SciPy, Plotly, etc.).
- Basic understanding of SQL for querying and working with data.
- Exposure to software development practices (version control with Git, debugging, documentation) is a plus.
- Coursework or experience with statistics, linear algebra, or numerical methods.
- Familiarity with machine learning concepts or frameworks (e.g., Scikit-learn, TensorFlow, Keras).
- Some experience from coursework, projects, or self-study in building or experimenting with models.
- Prior exposure to robotics systems, automation, or sensor data (through coursework, projects, or clubs) is a plus.
Responsibilities
- Assist in analyzing datasets from engineering systems, vehicle sensors, and other sources to uncover patterns and support predictive modeling efforts.
- Help design clear and visually appealing charts and dashboards using tools such as Matplotlib, Seaborn, Plotly, or Tableau to communicate findings.
- Contribute to the creation and maintenance of real-time dashboards that track key metrics and system performance.
- Support data cleaning, preprocessing, and organization tasks to make datasets ready for analysis.
- Write simple SQL queries and learn how to work with databases.
- Gain exposure to machine learning by assisting with model development and validation for autonomy applications
- Learn to apply scientific and engineering programming techniques to develop small data pipelines, automate processes, and run simulations.
Other
- Currently pursuing a Bachelor’s or Master’s degree in Mechanical Engineering, Mechatronics, Robotics, Electrical Engineering, Computer Science, or a related technical field.
- Interest in applying engineering and data analysis to solve real-world problems.
- Curiosity and analytical thinking to approach technical challenges.
- Ability to learn how to frame engineering problems as data science problems.
- Willingness to communicate findings clearly with technical and non-technical teammates.
