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
Qualifications
- 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
Job ID
Tesla’s mission is to accelerate the world’s transition to sustainable energy through increasingly affordable electric vehicles in addition to renewable energy generation and storage.
California-based Tesla is committed to having the best-in-class in safety, performance, and reliability in all Tesla cars. There are currently over 275,000 Model S, Model X and Model 3 vehicles on the road worldwide.
To achieve a sustainable energy future, Tesla also created infinitely scalable energy products: Powerwall, Powerpack and Solar Roof. As the world’s only vertically integrated energy company, Tesla continues to innovate, scale and reduce the costs of commercial and grid-scale systems, with the goal of ultimately getting us to 100% renewable energy grids.