EV Infrastructure Data Science Internship
Tesla Motors
North Holland, Amsterdam Zuid-Oost
6 dagen geleden

EV INFRASTRUCTURE DATA SCIENCE INTERN

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

With over 1200 Supercharger locations andseveral thousand destination charging sites around the world, Tesla’s charginginfrastructure aims to accelerate the world’s transition to sustainabletransportation by enabling electric mobility without compromises.

We use large-scale data analysis and machinelearning to retrieve actionable insights for enhancing the charging experience.

We also build the software tools and pipelines needed to maximize the leverageof these insights across our global operations.

Responsibilities

  • Include, but are not limited to :
  • Work closely with theglobal EV Infrastructure team to make data-driven decisions on chargingexpansion worldwide
  • Use statisticalmodeling and machine learning to gather insights on EV infrastructure usage andperformance
  • Build reliable, fast, anddynamic data tools and services
  • Develop visualizationtools for geospatial and temporal data sets
  • Develop monitoringKPI’s for tracking network performance
  • Minimum qualifications

    for EU and APAC)Business level proficiency in English

  • Currently pursuing aBachelor’s, Master’s or PhD in a related field (e.g., CS, Operations Research,Software Engineering, Statistics)
  • Strong programmingskills with a solid foundation in data structures and algorithms
  • Proficiency in Pythonand pydata stack (numpy, scipy, pandas, scikit-learn, flask)
  • Proficiency in SQLrelational databases and / or NoSQL databases
  • Experience withstatistical data analysis such as linear models and time series forecasting
  • Smart but humble, witha bias for action
  • Preferred qualifications

  • PhD studies in arelated field (e.g., CS, Operations Research, Software Engineering, Statistics)
  • Background instatistical learning with experience in using both supervised and unsupervisedmodels
  • Experience with Spark,Hadoop and / or streaming data
  • Experience in an agileworking environment
  • Quantitative projectsavailable online (github, blog posts, etc.)
  • Tesla participates in the

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