Senior Data Scientist
Service Engineering exists uniquely at the intersection of firmware/hardware design, service, diagnostics, manufacturing, quality, and reliability. Service Engineering multiplies efforts of service in the areas of diagnostics, repairs, and maintenance, while simultaneously reducing the need for each. As Service Engineering Platform Data Scientist, you will be responsible for data-driven decision making and data products on a wide variety of cross-functional projects within the global Service Engineering organization. You will have an integral part in critical projects that improve our products, support them in the field, and improve our diagnostics capabilities.
- Leverage artificial intelligence to automate the discovery of issues in the fleet.
- Use cutting edge big-data technologies to solve complex problems in a fast-paced environment.
- Develop scalable software to automate analytics and refine the tool set with which analytics are performed
- Are experts on Tesla data platforms and systems and drive the team as a whole to be more data-driven
- Extract insights from data, determine the best way to convey them to other people, and develop visualizations and/or other tools for self-service of those insights
- Research solutions from the latest literature and share your work with the broader Tesla data science community.
- Identify trends, invent new ways of looking at data, and get creative in order to drive improvements in both existing and future products
- Partner with Program Managers and leadership team to gather critical data to prioritize projects and measure success
- Develop efficient queries in SQL and leverage Spark to query the entire Tesla fleet.
- Give talks, contribute to open source projects, and advance data science on a global scale.
- Proficient in Python coding, software version control, and software testing with an attitude of fast iteration
- Experience in using Machine Learning tools, such as TensorFlow, PyTorch, scikit-learn etc.
- Demonstrated machine learning in an industry setting
- Proficient in SQL
- Strong foundation in statistics, probability, and experimental design
- Experience in one or more of the following data visualization tools such as Tableau, Apache Superset, Plotly
- Ability to explain complex concepts in data science to a wide variety of audiences.
- Deep understanding of distributed computing
- Experience with MapReduce, Spark, or other distributed computing framework
- Strong engineering fundamentals and intuition applied to firmware/software-enabled mechatronic systems
- Self-starter and great at navigating distributed teams; can work independently and find the best data sources to provide insights to the team
- Experience with safety critical systems and/or regulated industries is a plus
- Experience with NoSQL database such as MongoDB or Cassandra
- Knowledge of linux, VM deployment, and containerization
- Atlassian JIRA and Agile/SCRUM software development workflow familiarity preferred