Sr. Data Analyst, Commercial Service Operations

  • Tesla
  • Fremont, CA, USA
  • Dec 11, 2020
Full-time A/B Testing Analytics Computer Science Data Analysis Data Visualization MATLAB Python R SQL Statistics

Job Description

The Role

  • Collaborate with stakeholders to take a vague problem statement, refine the scope of the analysis, and use the results to drive informed decisions
  • Summarize and clearly communicate data analysis assumptions and results
  • Build data pipelines to feed data analyses into production dashboards that engineers can rely on
  • Understand and apply reliability concepts in your data analysis
  • Design and implement metrics, applications and tools that will empower energy service by allowing them to self-serve their data insights
  • Work with service managers to drive usage of your applications and tools
  • Write clean and tested code that can be maintained and extended by other software engineers
  • Maintain robust documentation and support your production applications
  • Keep up to date on relevant technologies and frameworks, and propose new ones that the team could leverage
  • Independently identify trends, invent new ways of looking at data, and get creative in order to drive improvements in both existing and future products

Required Skills

  • 2 - 5 years of experience in a data analytics or business data analytics related role
  • Experience building data visualizations hosted on existing web-based platforms (e.g. Kibana, Tableau, Superset)
  • Degree in Statistics, Economics, Computer Science, Physics, or a related quantitative field
  • Strong proficiency in Python and SQL with willingness to complete assessment
  • Deep statistical skills such as: A/B testing, analyzing observational data, and data modeling
  • Experience writing software in a professional environment
  • Strong problem-solving skills to help refine problem statements and solve them with the available data
  • Smart but humble, with a bias for action
  • Experience with data science tools such as: Pandas, Numpy, R, Matlab, and Octave preferred
  • Ability to build data pipelines and web applications preferred
  • Preferred experience within an Agile environment
  • Continuous integration and continuous deployment experience required
  • Dev -Ops experience is a plus (e.g. Linux, Ansible, Docker, and Kubernetes)
  • Understanding of reliability concepts (Weibull, Lognormal, Exponential, etc.), life data (or survival) analysis, and reliability modeling preferred


  • Advanced degree in Statistics, Economics, Computer Science, Physics, or a related quantitative field
  • Proven track record of leveraging massive amounts of data to drive product innovation
  • Experience with distributed analytic processing technologies (Spark, Presto, Hive)
  • Experience providing data solutions to business executives and stakeholders
  • Ability to self-start, possessing deep product sense
  • End-to-end experience with data, including querying, aggregation, analysis, and visualization using SQL

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