Principal Data Scientist
Newark, CA
Applications have closed
Lucid Motors
With extraordinary design, performance, range, convenience, and utility, Lucid Gravity is the future of sustainable mobility, reimagining the luxury electric SUV.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 them is a very exciting and challenging task. The Data Scientist at Lucid is setting data science foundation for our fast-growing data team, to enable the company tackle engineering and business challenges by designing analytics and AI solutions. This opportunity involves defining the path to discover trends, patterns and hidden insights from data while collaborating with the most brilliant talents in the automotive industry to build AI products.
Role
- Work on state-of-the-art large-scale data science and machine learning projects
- Design and architecture key AI products in automotive domain and lead the product implementation
- Help define the analytical direction and influence the direction of the Engineering teams.
- Use mathematical techniques to arrive at an answer using data. Translate analysis results into business recommendations.
- Partner with Engineering teams 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 engineering teams
- Use quantitative analysis and the presentation of data to see beyond the numbers and understand what can improve our processes.
- Engage broadly with the organization to identify, prioritize, frame, and structure complex and ambiguous engineering challenges, where advanced analytics, AI and machine learning can have the biggest impact.
Qualifications
- Advanced degree in Computer Science, Mechanical engineering, Statistics or related STEM field.
- 5+ years of Data or Machine learning Science experience working on highly complex problems in a dynamic setting
- Strong programming skills, especially in Python, or C/C++ with 5+ years of relevant experience in a programming intensive role.
- Technical expertise and in-depth knowledge in one or more of the following ML topics: Anomaly detection and signal processing, time-series data analysis and modeling, Conventional Machine Learning methods, Computer Vision, Deep learning, CNNs, Natural Language Processing (NLP), text mining, sentiment analysis, information retrieval, etc.
- Proficiency with a deep learning framework such as TensorFlow, Keras, Pytorch, Caffe, MXNet, etc.
- Relevant work experience, including experience applying advanced analytics, and data mining techniques.
- Experience with distributed computing platforms, particularly Kubernetes or the Hadoop/Spark ecosystem
- Experience with rules engine applications using distributed computing MapReduce, Spark, etc.
- Experience with data presentation and visualization with tools such as Tableau, Grafana and other similar tools.
- 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
- Excellent communication and presentation skills.
Nice to Haves
- Relevant experience in EV or Automotive and autonomous driving is a huge plus
- Experience with telematics data analytics and decision modeling is a plus
- Hands-on experience with cloud computing and HPC or other cloud and distributed platforms e.g. Spark, Airflow, Kubernetes, Kubeflow, MLFlow, etc. is a plus.
Tags: Airflow Autonomous Driving Big Data C++ Caffe Computer Science Computer Vision Data analysis Data Analytics Data Mining Deep Learning Engineering Grafana Hadoop HPC Keras Kubernetes Machine Learning MLFlow MXNet NLP Python PyTorch Scala Spark Statistics STEM Tableau TensorFlow
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