Responsibilities:
- Lead the development and implementation of complex data models and algorithms to solve business problems for the Perception team and beyond.
- Develop and implement data strategies for collecting, sampling, labeling, and using large scale datasets to enhance machine learning model performance.
- Develop metrics and tools for anomaly detection and trend analysis in data from various sources, including real-world vehicle platforms and simulations.
- Design and improve scalable data pipelines and automation for machine learning and performance evaluation.
- Prepare and present detailed reports and visualizations to stakeholders, clearly communicating complex results to both technical and non-technical audiences.
- Stay current with advancements in data science and machine learning technologies, driving the adoption of best practices.
- Act as an advisor and influence collaborators across multiple teams, fostering a culture of continuous improvement.
Qualifications:
- MS or PhD in a quantitative field (e.g. Statistics, Mathematics, Physics)
- 3+ years of experience solving large-scale data science problems
- Experience with theoretical aspects of data science and machine learning (deep learning, statistical analysis, and mathematical modeling)
- Experience in building machine learning algorithms and infrastructure, such as: data pre- and post-processing, sampling and curation, ablation studies, evaluation
- Experience with Python and SQL data analysis libraries and packages
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