O'Reilly Auto Parts is looking to solve business problems and significantly influence the future of data science and AI innovation for the entire company
Requirements
- Experience in software development and data science, with a focus on AI/ML applications and mathematical modeling
- Visionary expertise in advanced data science, machine learning, and AI concepts, pushing the boundaries of current capabilities
- Deep knowledge of diverse ML architectures, including cutting-edge research trends
- Proven track record of designing and implementing innovative, enterprise-scale data science solutions on cloud platforms like GCP and Azure, leveraging its full suite of advanced ML capabilities
- Exceptional proficiency in Python for highly complex, performant, and scalable AI development
- Architectural expertise in cloud-native ML platforms (e.g., GCP, Vertex AI) and integration with large-scale data ecosystems
- Deep understanding of MLOps, AIOps, and production ML system design at an enterprise level
Responsibilities
- Define strategy for the end-to-end lifecycle of critical, enterprise-level AI/ML projects, setting architectural standards and future-proofing deployment methodologies
- Drive innovation in designing and implementing advanced, responsible AI validation frameworks with a focus on fairness, transparency, accountability, and explainability, influencing best practices from industry
- Influence cross-functionally with MLOps, Data Engineering, Application Engineering and Platform teams to establish enterprise-wide standards for scalable, low-latency deployment, advanced CI/CD, and robust lifecycle management across all AI initiatives
- Define Strategy for the organization's approach to scalable, sophisticated data science and machine learning solutions, identifying strategic opportunities leveraging GCP, Vertex AI, BigQuery ML, emerging technologies or other cloud platforms
- Drive innovation in the development of next-generation predictive models and analytical frameworks that provide significant competitive advantage
- Define strategy for the approach to deep exploratory data analysis (EDA), leveraging cutting-edge tools and methodologies to uncover transformative patterns, correlations, and anomalies in massive, diverse datasets
- Influence cross-functionally to shape enterprise-wide data collection, curation, and governance strategies based on insights from complex data landscapes
Other
- Advanced degrees (Ph.D.) in relevant quantitative fields
- Experience in strategic consulting or advisory roles
- Plans, organizes, prioritizes and oversees activities to efficiently meet objectives
- Plans, identifies, monitors, analyzes, and prioritizes risks (threats and opportunities), creates response plans, and manages the risk if it occurs
- Travel requirements not specified, but position can be worked remotely in the United States
