Data Analytics Intern (Spring 2027)
Zipline · San Francisco, United States · 15d ago
About Zipline
Zipline is the world’s largest and most experienced drone delivery service. We are on a mission to serve all humans equally by ensuring access to food, medicine and essential goods anytime, anywhere. We design, build, and operate the world’s largest autonomous logistics system, delivering critical supplies quickly and reliably. Today, Zipline operates on four continents, makes a delivery somewhere in the world every 30 seconds, and has completed millions of deliveries to date, including blood, vaccines, medical supplies, food, and retail products.
Our customers include the world’s largest and most prominent healthcare systems, governments, retailers, restaurants and global businesses who rely on us to save lives, reduce emissions, increase economic opportunity, and provide delivery from point A to point B as fast as possible. The drone is only 15% of what we’ve built to enable seamless, reliable, global operations.
Our system strengthens supply chains, reduces congestion, and gives people time back. With more than 140 million commercial autonomous miles safely flown, Zipline is redefining access to healthcare, consumer products, and food across the globe.
We operate at a global scale and are looking for practical problem solvers who thrive on real-world challenges and rapid growth. Our team is motivated by building systems that have a direct, meaningful impact on people’s lives and by scaling the future of logistics. We are seeking people who sculpt from first principles, enjoy facing adversity, and can do the impossible at record breaking speeds.
About the Integration, Quality & Manufacturing Engineering Team
Zipline's Integration, Quality & Manufacturing Engineering (IQME) team keeps the factory floor running smoothly. We're responsible for making sure the right parts and materials are always in the right place at the right time, from receiving and warehouse storage, to staging materials right at the production line, to getting finished goods ready to ship.
We work hand-in-hand with Production, Quality, Supply Chain, and Material Planning to build and improve the drones, and we're currently standing up brand-new production lines as we scale fast. We're also focused on using better data from production, inventory, and quality data pulled from systems like our ERP, MES, and traceability tools, to help everyone on the floor make smarter, faster decisions.
About the Data Analytics Intern Role
As a Data Analytics Intern on the IQME team, you'll dive into the data behind how Zipline actually builds and ships its drones, from inventory and materials to production output and quality.
You'll team up with engineers, production leads, quality stakeholders, and leadership to find insights that keep the factory floor running smoothly. Your main focus will be turning data into insights that help people make faster, smarter decisions on the floor.
This role is ideal for someone passionate about data, problem-solving, and seeing their analysis translate directly into real operational impact. Along the way, you'll learn from a fast-scaling manufacturing team, giving you a front-row seat to how data drives decisions in a mission-driven environment.
What You'll Do
- Collaborate with production, quality, and supply chain teams to understand what data and insights matter most to the business
- Partner with engineers to learn how manufacturing and inventory data is generated and transformed so it's ready for analysis
- Write SQL queries and help streamline reporting using Mode, Streamlit or Sigma.
- Support data quality efforts by validating datasets and catching issues before they affect reporting
- Dig into open-ended questions from the floor and leadership, turning raw data into clear, actionable answers
What You'll Bring
- Currently pursuing a bachelor’s degree in Data Analytics, Data Science, Computer Science, Engineering, or a related field
- Comfortable writing SQL queries to calculate metrics and pull insights from data
- Some experience with Python for data analysis (scripts, cleaning, or automation)
- Experience working with large datasets and turning them into clear findings
- Familiarity with a BI/dashboarding tool such as Mode, Sigma, Tableau, Looker, ThoughtSpot, or Power BI
- Strong communication skills - able to explain data findings simply and tell a clear story with numbers
- Solid analytical and problem-solving skills, with the ability to translate business questions into technical solutions
What Else You Should Know
This internship is a full-time position, in-person at our South San Francisco office. We will host our Spring 2027 interns from January to April. Zipline is unable to sponsor work visas for applicants to this position.
Additional benefits may include relocation support, a housing stipend, overtime pay, paid sick time, and other benefits, where applicable and subject to local requirements.
Candidates are limited to three (3) applications within a 30-day period.
Zipline is an equal opportunity employer and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws or our own sensibilities.
Zipline is also committed to providing reasonable accommodations to individuals with disabilities. Please let your point of contact at Zipline know if you require any accommodations throughout your interview process.
Voluntary Self-Identification
For government reporting purposes, we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file.
As set forth in Zipline ’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.