Senior Reliability Data Scientist / Software Engineer

Key Skills

Analytical and Problem solving, Apache Airflow, Big Data Technology, CDASH, Data Lake, Data pipelines, Data science techniques, Data Visualization, Data Warehousing, Docker, ETL frameworks, Flask, Java Programming, Machine learning techniques, Mathematics, matplotlib, MLOps tools, plotly, Presto, Python Programming, Sampling methods, Server architectures, SPARK Programming, SQL, Tableau

Job Description

The reliability data team is looking for strong Data Scientist/Software Engineers to utilize large-scale data and help Tesla engineers design and validate the most compelling and reliable products for our customers. The team collects real-time life data from fleets of Vehicle & Energy products coupled with accelerated life testing data to develop pipelines, software and reliability models. The role is high impact driving Powertrain & Energy Warranty modeling as well as reliability statistics, physics of failure, and electronics prognostics analyses across Tesla products.

What You’ll Do

• Develop robust, flexible and automated software tools to enable complex analysis of real-time fleet
• Apply statistical analysis to test (accelerated life) and field (life) data to inform reliability physics modeling/analyses and associated corrective actions
• Work closely with Reliability and Design engineers to create/interpret/validate numeric models of fielded and in-test products
• Contribute to the automation and standardization of Tesla data pipelines
• Build visualizations to effectively communicate analysis results
• Answer complex questions on fleet usage and behavior to enable proactive monitoring, grow reliability, and minimize field failures

What You’ll Bring

• Bachelor’s degree or higher in quantitative discipline (Statistics, Computer Science, Mathematics, Physics, Electrical Engineering) or the equivalent in experience and evidence of exceptional ability
• Strong Proficiency in Python (Data Science stack)
• Strong knowledge of data structures, architectures and languages such as SQL
• Solid understanding of statistics (Maximum Likelihood Estimation, Bayesian methods, Monte Carlo analysis, Weibull distribution...)
• Working knowledge of the Big Data ecosystem (Spark, Presto, Data lake/Warehouse)
• Working Knowledge of Date Pipelining (Airflow Pipelines, ETL, Spark Data Analyses)
• General knowledge of physics and engineering principles
• Experience and interest in data visualization techniques (e.g. Matplotlib, Tableau, Plotly…)
• Ability to problem solve and adjust priorities with little advance notice to meet deadlines
• Strong verbal and written communication skills Nice to have
• Experience developing predictive models on time-series data
• Experience with MLOps and building machine learning pipelines (clustering analysis, failure prediction, anomaly detection)
• Experience with containerization (e.g Docker)
• Experience with quick web application development (e.g Flask, Dash, Streamllit)

Tesla is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state or local laws.