Principal Data Scientist

Key Skills

Algorithms, Apache Airflow, Apache Hadoop, Caffe, Data Analytics, Data Mining, Data science techniques, Deep Learning, Effective communication skills, Keras software library, Kubeflow, Kubernetes-K8s, Large Language Models - LLMs, Machine learning techniques, MapReduce, MLflow, Natural Language Processing (NLP), Presentation skills, PyTorch, Spark Core, TensorFlow

Job Description

At Lucid, we set out to introduce the most captivating, luxury electric vehicles that elevate the human experience and transcend the perceived limitations of space, performance, and intelligence. Vehicles that are intuitive, liberating, and designed for the future of mobility.

We plan to lead in this new era of luxury electric by returning to the fundamentals of great design – where every decision we make is in service of the individual and environment. Because when you are no longer bound by convention, you are free to define your own experience.

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.

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.

The Role

• Work on state-of-the-art large-scale data science and machine learning projects
• Design and architecture key AI products in automotive and EV 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), Large Language Models (LLM), 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, Superset, 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
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