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Data Analyst, Energy Field Quality
Company | Tesla |
Address | , Palo Alto, Ca |
Employment type | FULL_TIME |
Salary | |
Expires | 2023-07-19 |
Posted at | 11 months ago |
What to Expect
What You’ll DoWhat You’ll Bring
The Tesla Energy Products Field Quality team is looking for a passionate and collaborative Analyst to join the team and leverage data and analytics to ensure the best customer experience and fleet reliability across the Tesla Energy portfolio; Industrial, Residential, Supercharger, and Solar. In the Energy Products Field Quality Data Analyst role, you will identify fleet-wide part performance trends, operation, and maintenance challenges across the growing fleet of energy products. The Fleet Analyst’s primary role is to leverage real-world performance and maintenance data to drive fleet-wide improvements by identifying trends and determining effective strategies to improve key fleet health metrics. This position is well suited for curious, inventive, and adventurous analysts who want to solve problems with data and aren’t afraid to venture into the unknown and untested when required. As part of the team, you will be enabled to work across the organization to solve problems and ensure the success of our products working alongside Industrial Energy, Residential Energy, and Solar Product and Service Engineering. Our teams operate with a non-conventional philosophy of inter-disciplinary collaboration. Each member of the team is expected to challenge and to be challenged, to create, and to innovate. We’re tackling the world’s most difficult and important problems—and we wouldn’t succeed without our shared passion for making the world a better place.
What You’ll Do
- Create data visualizations to communicate analysis results and drive decision making
- Perform correlation studies between manufacturing data and field performance to develop screening tests
- Perform statistical analysis to quantify reliability risks in the field and identify emerging trends
- Utilize fleet data for diagnostics and prognostics
- Strong Python, especially in a data analytics/science capacity where pandas/numpy are used heavily
- Any opensource/freeware viz tools (e.g., D3, ggplot)
- Ability to quickly learn new technologies
- BS in Computer Science, Physics, Electrical Engineering, or proof of exceptional skills in related fields.
- Python (matplotlib/seaborn/plotly/etc.)
- Strong SQL, comfortable writing queries, data processing scripts, and understanding RDBMS data structures
- Able to visualize data effectively
- Tableau (or, similar BI tools)
- Strong analytical skills and knowledge of applied statistics including predictive analytics, time series analysis and machine learning. Working knowledge of reliability statistics such as Weibull Analysis preferred
- Exposure to "big data" technologies, particularly any part of a Spark, HBASE, Hadoop stack
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