Data Scientist, Charging Data and Modeling

Job Description

We are the team that uses data analytics to bridge the engineering, service, and deployment of Tesla’s charging infrastructure and to enhance the charging experience worldwide.

With over 1200 Supercharger locations and several thousand destination charging sites around the world, Tesla’s charging infrastructure aims to accelerate the world’s transition to sustainable transportation by enabling electric mobility without compromises.

We use large-scale data analysis and machine learning to retrieve actionable insights for enhancing the charging experience. We also build the software tools and pipelines needed to maximize the leverage of these insights across our global operations.

Responsibilities

Include, but are not limited to:

• Use statistical modeling and machine learning to extract insights on fleet usage, trends, performance
• Leverage insights to inform planning and optimization of the EV infrastructure
• Build reliable, fast, and dynamic data tools, pipelines, and web services
• Develop visualization tools for geospatial and temporal datasets
• Develop monitoring KPI’s for tracking network performance

Minimum qualifications

• Bachelor’s, Master’s or PhD in a related field (e.g., CS, Operations Research, Software Engineering, Statistics)
• Strong programming skills with a solid foundation in data structures and algorithms
• Proficiency in data analysis, modeling, and web services in Python
• Proficiency in SQL relational databases and/or NoSQL databases
• Experience with statistical data analysis and machine learning such as linear models, time-series forecasting, or neural networks
• Smart but humble, with a bias for action

Preferred qualifications

• Background in statistical learning with experience in using both supervised and unsupervised models
• Experience with Spark, Hadoop and streaming data
• Experience in an agile working environment
• Experience working in a global team
• Quantitative projects available online (github, blog posts, etc.)

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