This internship position is part of the Charging Data Modeling team at Tesla, focusing on developing models and algorithms to enhance the customer charging experience. The role involves using statistical analysis and large-scale data to inform decisions about Tesla's EV charging infrastructure. Interns will work on designing algorithms for fleet orchestration and contribute to Tesla's robotaxi simulation platform. This position is ideal for students pursuing degrees in quantitative fields and offers a chance to impact the future of autonomous fleets.

• Currently pursuing a Bachelor’s, Master’s, or PhD in a quantitative field such as Math, Economics, Statistics, Computer Science, Operations Research, or Engineering with a graduation date between December 2026 and December 2027.
• Strong programming skills with a solid foundation in data structures and algorithms.
• Proficiency in data analysis and modeling in Python; experience with Golang and collaborative code development is a plus.
• Proficiency in SQL (relational databases) and/or NoSQL databases.
• Experience with statistical data analysis and machine learning.
• Ability to clearly communicate insights to cross-functional teams.
• Experience with time-series or geospatial datasets.
• Experience with experiment design and causal inference methods.
• Experience with Spark, Hadoop, or streaming data.
• Background in optimization techniques applied to fleet, logistics, or energy problems.

• Use statistical analysis and large-scale data to extract insights on fleet usage, charging trends, performance, and customer behavior.
• Improve data-driven decision making through rigorous analysis, machine learning modeling, and clear communication with stakeholders.
• Leverage insights to inform planning, siting, timing, and optimization of Tesla’s EV charging infrastructure.
• Design, prototype, and help productionize algorithms that drive customer-facing UI features and pricing signals.
• Develop charging-aware fleet orchestration algorithms that help determine when, where, and how vehicles should charge.
• Contribute to Tesla’s robotaxi simulation platform to evaluate charging strategies, stress-test algorithms, and validate results against real fleet data.
• Contribute to Tesla’s vehicle algorithms to predict energy consumption and recommend optimal charging locations.
• Build reliable, fast, and dynamic data tools and pipelines that support modeling and decision systems at fleet scale.
• Collaborate cross-functionally to turn analytical insights into product, operational, and algorithmic decisions.

• Employees at Tesla are often offered day-one coverage with multiple medical options (some at $0 paycheck cost), dental/vision, company HSA contributions, a 401(k) match, and equity programs. Most roles also include paid time off and holidays, family-building support, employee assistance, commuter and childcare benefits, and access to discounts and wellness programs.