Sr. Data Scientist, Predictive Maintenance

Newark, CA

Applications have closed
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Lucid Motors

Leading the future of luxury mobility
Lucid’s mission is to inspire the adoption of sustainable energy by creating the most captivating luxury electric vehicles, centered around the human experience. Working at Lucid Motors means having a shared vision to power the future in revolutionary ways. Be part of a once-in-a-lifetime opportunity to transform the automotive industry.
The Data Science and Machine Learning team at Lucid is on the mission to design, develop, and deploy AI solutions to help make safe and sustainable products and services on par with Lucid’s Luxury brand. Data generated by electric vehicles is rich and diverse and driving insight from it is a very exciting and challenging task. This opportunity involves creating end-to-end AI solutions from design and development to delivery of data-driven services and products utilizing AI, big data, cloud, and edge computing.

Role

  • Design and develop data science pipeline using PySprak, Scala, SQL for parallel processing.
  • Drive predictive analytics from billions of time series data points
  • Help define the analytical direction and influence the direction of the associated engineering and infrastructure work.
  • Articulate business questions and use mathematical techniques to arrive at an answer using data. Translate analysis results into business recommendations.
  • Partner with internal stakeholders on projects to identify and articulate opportunities, see beyond the data to identify solutions that will raise the bar for decision making.
  • Extract actionable insights from broad, open-ended questions
  • Adapt machine learning and data mining algorithms to solve problems across several teams
  • Use quantitative analysis and the presentation of data to see beyond the numbers and understand what can improve our processes.
  • Lead projects with hands-on analysis and modeling, drawing from multiple analytical methods to choose the right tool and right level of complexity appropriate for the challenge.
  • Engage broadly with the organization to identify, prioritize, frame, and structure complex and ambiguous challenges, where advanced analytics projects or tools can have the biggest impact.

Qualifications

  • Ph.D. or Masters in Computer Science, Statistics, Operations Research or related field.
  • 8+ years experience as a Data Scientist
  • Experience with PySpark and other big data tools to create horizontally scalable solutions.  
  • Expert in time-series data and model building.
  • Experience with data presentation and visualization with tools such as Tableau, Zeppelin and other similar tools.
  • Relevant work experience, including experience applying advanced analytics, data mining and ML models.
  • Proven track record of developing and deploying algorithms for a production-ready recommendation, data mining or prediction systems using languages and big data platforms such as Scala, Python, Java, Spark, Presto, and Hive
Be part of something amazing
Come work alongside some of the most accomplished minds in the industry. Beyond providing competitive salaries, we’re providing a community for innovators who want to make an immediate and significant impact. If you are driven to create a better, more sustainable future, then this is the right place for you.
At Lucid, we don’t just welcome diversity - we celebrate it! Lucid Motors is proud to be an equal opportunity workplace and is an affirmative action employer.  We are committed to equal employment opportunity regardless of race, color, national or ethnic origin, age, religion, disability, sexual orientation, gender, gender identity and expression, marital status, and any other characteristic protected under applicable State or Federal laws and regulations.
To all recruitment agencies: Lucid Motors does not accept agency resumes. Please do not forward resumes to our careers alias or other Lucid Motors employees. Lucid Motors is not responsible for any fees related to unsolicited resumes. 
Job region(s): North America
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