Job Specifications
The Principal Data Scientist advises stakeholders and executives, provides technical leadership across the organization, executes large complex data science projects to solve business problems and significantly influences the future of data science and AI innovation for the entire company. Role requires knowledge of tools and methods, including statistics, artificial intelligence, and machine learning, at an advanced level.
This position can be worked remotely in the United States.
Responsibilities And Duties
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.
Define Strategy for the alignment of all modeling efforts with the enterprise-wide data strategy, long-term business objectives, and emerging technological trends.
Drive Innovation in architectural design, MLOps pipelines, and data governance, establishing the foundational principles for the organization's analytics and modeling capabilities.
Influence cross-functionally with executive leadership and key business stakeholders to identify and define the most impactful, often ambiguous and unstructured, enterprise-level business problems solvable through advanced data science.
Define strategy for data-driven recommendations that influence business decisions, long-term investments, and generate ROI. Act as a primary thought-leader and strategic advisor for algorithm-based recommendations across all aspects of the retail business.
Define Strategy for continuous learning and development across the data science organization, fostering a culture of intellectual curiosity and innovation. Stay at the forefront of AI/ML research and industry trends.
Mentor senior and junior scientists, establish mentorship programs, and significantly contribute to building the technical leadership and innovation culture of the entire data science community. Peer review and publish work in top tier ML/AI conferences such as NIPS, ICML, AAAI and COLT.
Define strategy for comprehensive QA and responsible AI testing methodologies across the enterprise, including designing frameworks for ethical AI audits, advanced model validation, and proactive drift detection.
Drive innovation in the adoption of advanced tools like Vertex Model Monitoring and custom CI/CD pipelines for highly automated and robust testing at scale.
Define strategy for knowledge management, documentation standards, and reproducibility across the entire data science function, ensuring long-term institutional knowledge and efficient collaboration.
Influence cross-functionally to implement tools and processes that facilitate seamless knowledge transfer and version control.
Define strategy for communicating complex model outputs into transformative, actionable business insights for the business stakeholders, directly influencing strategic decision-making and organizational direction.
Drive innovation in storytelling with data, leveraging advanced visualization techniques and fostering a data-driven culture across the organization.
Define strategy for the organization's approach to solving the most challenging, ambiguous, and high-impact business problems using novel algorithms and state-of-the-art AI frameworks (e.g., TensorFlow, PyTorch, HuggingFace).
Drive innovation and lead research and development efforts in solving business opportunities across enterprise such as supply chain optimization, personalized consumer experiences, and enhanced operational efficiency.
Skills
Required:
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 boundar
About the Company
O'Reilly Auto Parts started as a single store and has grown into a leading retailer in the automotive aftermarket industry with more than 6,100 locations and counting. With more than 94,000 team members, O'Reilly has expanded into 48 states, Puerto Rico, Mexico, and Canada. O'Reilly, headquartered in Springfield, Missouri, has a deep commitment to serving our customers, community, and our team members. Our culture values make O'Reilly the best place to work and grow! Whether you're interested in running a local store, managi...
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