<p><b>The Principal Data Scientist </b>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.</p><p></p><p><u><b>This position can be worked remotely in the United States. </b></u></p><p></p><p><b><span>Responsibilities and Duties:</span></b></p><p></p><ul><li><b>Define strategy </b>for the end-to-end lifecycle of critical, enterprise-level AI/ML projects, setting architectural standards and future-proofing deployment methodologies.</li><li><b>Drive innovation</b> in designing and implementing advanced, responsible AI validation frameworks with a focus on fairness, transparency, accountability, and explainability, influencing best practices from industry.</li><li><b>Influence cross-functionally</b> 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.</li><li><b>Define Strategy for</b> 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.</li><li><b>Drive innovation</b> in the development of next-generation predictive models and analytical frameworks that provide significant competitive advantage.</li></ul><ul><li><b>Define strategy f</b>or 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.</li><li><b>Influence cross-functionally </b>to shape enterprise-wide data collection, curation, and governance strategies based on insights from complex data landscapes.</li><li><b>Define Strategy</b> for the alignment of all modeling efforts with the enterprise-wide data strategy, long-term business objectives, and emerging technological trends.</li><li><b>Drive Innovation </b>in architectural design, MLOps pipelines, and data governance, establishing the foundational principles for the organization's analytics and modeling capabilities.</li><li><b>Influence cross-functionally</b> 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.</li><li><b>Define strategy</b> 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.</li><li><b>Define Strategy </b>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.</li><li><b>Mentor</b> 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.</li><li><b>Define strategy</b> 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.</li><li><b>Drive innovation i</b>n the adoption of advanced tools like Vertex Model Monitoring and custom CI/CD pipelines for highly automated and robust testing at scale.</li><li><b>Define strategy </b>for knowledge management, documentation standards, and reproducibility across the entire data science function, ensuring long-term institutional knowledge and efficient collaboration.</li><li><b>Influence cross-functionally</b> to implement tools and processes that facilitate seamless knowledge transfer and version control.</li><li><b>Define strategy</b> for communicating complex model outputs into transformative, actionable business insights for the business stakeholders, directly influencing strategic decision-making and organizational direction.</li><li><b>Drive innovation</b> in storytelling with data, leveraging advanced visualization techniques and fostering a data-driven culture across the organization.</li><li><b>Define strategy</b> 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).</li><li><b>Drive innovation</b> and lead research and development efforts in solving business opportunities across enterprise such as supply chain optimization, personalized consumer experiences, and enhanced operational efficiency.</li></ul><p></p><p><b>Skills:</b></p><p></p><p><b>Required:</b></p><p></p><ul><li><b>Experience in software development and data science, with a focus on AI/ML applications and mathematical modeling. </b></li><li>Visionary expertise in advanced data science, machine learning, and AI concepts, pushing the boundaries of current capabilities.</li><li>Deep knowledge of diverse ML architectures, including cutting-edge research trends.</li><li>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 (e.g., custom Vertex AI operations, distributed training).</li><li>Exceptional proficiency in Python for highly complex, performant, and scalable AI development.</li><li>Architectural expertise in cloud-native ML platforms (e.g., GCP, Vertex AI) and integration with large-scale data ecosystems.</li><li>Deep understanding of MLOps, AIOps, and production ML system design at an enterprise level.</li><li>Ability to innovate and define industry-leading best practices for responsible AI, model governance, and ethical deployment.</li><li>Expertise in designing complex experimental frameworks for large-scale impact measurement.</li><li>Exceptional ability to influence executive-level strategy and investment decisions through compelling data-driven insights.</li><li>Deep understanding of the retail tech industry and its challenges, capable of identifying transformative opportunities for AI.</li><li>Recognized thought leader in the data science community, internally and externally.</li><li>Ability to mentor and technically advise Senior and other Principal-level data scientists.</li><li>Proven experience in building and fostering a culture of innovation and scientific rigor.</li></ul><p></p><p><b>Preferred:</b></p><ul><li>Expertise in Python, R, SQL, Scala, and relevant machine learning and deep learning libraries/packages such as NumPy, Pandas, SciKit-Learn, TensorFlow, Keras, and PyTorch.</li><li>Significant publications (NIPS, ICML, AAAI, COLT) or patents in AI/ML.</li><li>Experience contributing to or leading open-source ML/AI projects.</li><li>Advanced degrees (Ph.D.) in relevant quantitative fields.</li><li>Experience in strategic consulting or advisory roles.</li><li>Past experience in solving complex business problems using vision models, natural language processing (NLP), slow mover forecasting models, and recommender systems.</li></ul><ul><li>Plans, organizes, prioritizes and oversees activities to efficiently meet objectives.</li><li>Plans, identifies, monitors, analyzes, and prioritizes risks (threats and opportunities), creates response plans, and manages the risk if it occurs.</li></ul><p style="text-align:left">O’Reilly Auto Parts has a proven track record of growth and stability. O’Reilly is full of successful career stories and believes in a strong promote-from-within philosophy, encouraging you to grow your career along with the organization. </p><p style="text-align:inherit"></p><p style="text-align:left"><b>Total Compensation Package:</b></p><ul><li><p style="text-align:left">Competitive Wages & Paid Time Off</p></li><li><p style="text-align:left">Stock Purchase Plan & 401k with Employer Contributions Starting Day One</p></li><li><p style="text-align:left">Medical, Dental, & Vision Insurance with Optional Flexible Spending Account (FSA)</p></li><li><p style="text-align:left">Team Member Health/Wellbeing Programs</p></li><li><p style="text-align:left">Tuition Educational Assistance Programs</p></li><li><p style="text-align:left">Opportunities for Career Growth</p></li></ul><p></p><p><i>O’Reilly Auto Parts is an equal opportunity employer. </i><i><span>The Company does not discriminate on the basis of race, religion, color, national origin or ancestry (including immigration status or citizenship), sex, sexual orientation, gender identity, pregnancy (including childbirth, lactation, and related medical conditions,) age (40 and over), veteran status, uniformed service member status, physical or mental disability, genetic information (including testing or characteristics) or another protected status as defined by local, state, or federal law, as applicable.</span></i></p><p></p><p><i>Qualified individuals with a disability may be entitled to reasonable accommodation under the Americans with Disabilities Act. If you require a reasonable accommodation during the application or employment process, please send an email to: </i><a href="mailto:rar@oreillyauto.com" target="_blank"><i><span>rar@oreillyauto.com</span></i></a><i> or call 417-862-2674, ext. 68901, and provide your requested accommodation, and position details. </i></p>
