Data Scientist - Manufacturing Quality Systems 6/5/2020
JOB DESCRIPTIONAPPLY Role
The quality data science team is responsible for performing advanced analytics, creating infrastructure and data pipelines, developing predictive models and making data applications that enable cross functional teams to leverage a wealth of manufacturing, equipment and vehicle data both efficiently and effectively. In this role, you will develop an anomaly detection system for equipment, products and systems and apply statistical and machine learning models to early predict failures and take proactive actions. Moreover, you will build software to support quality throughout the product lifecycle, and contribute to data platform infrastructure ensuring reliability and robustness.
* Design and develop anomaly detection platform for creating, tracking and applying statistical and machine learning models in a production environment.
* Create and refine models to maximize accuracy and impact, engage stakeholders and rapidly iterate based on feedbacks.
* Design and develop ETLs, data pipelines, automation systems and APIs for retrieving, processing, analyzing, and visualizing batch and real time data.
* Analyze manufacturing, equipment and vehicle data and extract useful statistics and insights about failures in order to early predict issues and take proactive actions.
* Engage with cross functional teams to identify data sources where the potential value is not fully realized and invent new means with which to interact and gather insights from them.
* Master s degree or higher in quantitative discipline (e.g. Statistics, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering) or the equivalent in experience and evidence of exceptional ability
* 5+ years of work experience in data analytics, data engineering, data science, machine learning or related fields
* Extensive experience writing software with Python
* Experience with multiple data architecture paradigms (e.g. MySQL, MicrosoftSQL, Oracle, MongoDB, Kafka, Hadoop, Hbase, Spark)
* Experience with infrastructure and continuous integration pipelines (e.g. Docker, Kubernetes, Airflow, Jenkins)
* Experience with open source machine learning libraries and frameworks (e.g. Scikit-Learn, Tensorflow, PyTorch, Keras) and introduce accurate models to a production environment
* Experience with data visualization techniques and tools (e.g. Matplotlib, Plotly, Superset, Tableau), quick web application experience preferred (e.g. Flask, JQuery, Streamlit, Angular 2+)
* Knowledge of various data communication protocols (e.g. REST API, gRPC, Websockets)
* Able to work under pressure while collaborating and managing competing demands with tight deadlines
* A passion for machine learning and a results-oriented mindset
Tesla participates in the E-Verify Program
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.