Data Science / Data Engineer Intern

Join Hadrian, a mission-driven industrial company, as a Data Science/Data Engineer Intern. You'll work alongside experienced engineers and analysts on real production data, building and maintaining data pipelines, analyzing production data, and developing dashboards and metrics. This hands-on role will directly influence operational decisions at Hadrian and provide valuable experience in data infrastructure and analysis for a high-growth company.

• Construire et maintenir des pipelines de données qui déplacent les données de machine, de production, de qualité et de programme du sol de l'usine vers notre entrepôt.
• Modéliser et structurer des ensembles de données sur lesquels les équipes d'ingénierie, d'exploitation et de qualité s'appuient pour la prise de décision quotidienne.
• Analyser les données de production pour faire ressortir des informations sur le débit, la capacité, le temps de cycle, le rendement et l'utilisation des machines.

• Comfortable working in a fast-moving, highly ambiguous environment
• Proficiency in Python and SQL
• Strong problem-solving skills and the ability to work through ambiguous technical challenges
• Strong attention to detail and follow-through
• Clear written and verbal communication, including the ability to explain analysis to non-technical partners
• Familiarity with data pipelines, ETL/ELT workflows, or cloud data warehouses
• Internships are available for our Fall 2026, Spring 2027, and Summer 2027 cohorts. Indicate your preferred term(s) when applying
• Willingness to work on-site in Los Angeles, CA
• Current university student pursuing a Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Applied Math, Engineering, or a related field, with an expected graduation date between December 2027 and June 2028
• Working knowledge of statistics and the ability to turn a messy dataset into a defensible conclusion
• Prior internship or project experience building production data pipelines or shipping analysis that changed a decision
• Experience with orchestration or transformation tooling
• Exposure to time-series, sensor, or telemetry data
• Interest in manufacturing systems, automation, or industrial software