Principal Data Scientist – Supply Chain Operations

Job Description Uses advanced experimental design, statistics, technologies, and (e.g., machine learning, natural language processing) to discover and understand data patterns and trends to generate actionable insights and solutions for client services, product enhancement, and business impact. Engages in training, deploying, and monitoring machine learning models, and in architecting solutions for the entire model lifecycle. Optimizes prompts. Summarizes and interprets data and analysis insights and findings to make recommendations to stakeholders. Implements Extract, Transform, Load (ETL) for data pipelines while ensuring data security and privacy. Develops efficient and scalable code and tests. Maintains familiarity with current developments in the data science field and integrates knowledge into model development. Role is on-site in Nashville, TN or Austin, TX. Responsibilities Data Automation & AI Solutions Design, build, and maintain scalable data automation solutions supporting OCI's global supply chain. Develop AI and machine learning models that improve forecasting, inventory optimization, supply planning, logistics execution, manufacturing readiness, and operational performance. Identify opportunities to eliminate manual processes through automation, predictive analytics, and intelligent workflows. Build reusable automation frameworks and data products that improve operational efficiency and business scalability. Evaluate emerging AI and automation technologies and recommend practical applications across supply chain operations. Data Engineering & Analytics Design and develop robust data pipelines, models, and architectures that support real-time operational reporting and advanced analytics. Build scalable datasets that enable forecasting, planning, inventory management, supplier performance, and deployment execution. Ensure data quality, governance, reliability, and accessibility across multiple enterprise systems. Develop dashboards, scorecards, and self-service analytics that improve operational visibility across global supply chain functions. Collaborate with engineering teams to integrate data across Oracle Fusion Cloud Applications, operational systems, and cloud platforms. Operational Intelligence Develop operational dashboards, KPI frameworks, and control tower capabilities that provide end-to-end visibility into supply chain performance. Create intelligent alerting mechanisms that proactively identify operational risks, exceptions, and bottlenecks. Build predictive models supporting scenario planning, capacity management, supplier performance, and deployment readiness. Translate complex operational data into actionable insights that support day-to-day execution and long-term planning. Cross-Functional Collaboration Partner with Supply Planning, Procurement, Manufacturing, Logistics, Capacity Management, and Data Center Operations teams to understand business challenges and develop scalable technical solutions. Collaborate with product managers, engineers, and business stakeholders to define analytics requirements and deliver impactful data solutions. Provide technical guidance and subject matter expertise for automation initiatives and enterprise data projects. Influence best practices for data engineering, analytics, and automation across the organization. Continuous Improvement Drive improvements in data quality, automation, reporting accuracy, and operational efficiency. Identify opportunities to simplify processes, reduce technical debt, and improve maintainability of data platforms. Document technical designs, data models, and automation solutions to support long-term scalability and operational excellence. Stay current on emerging technologies in AI, machine learning, cloud computing, and data engineering. Experience Required Qualifications 7–10+ years of experience in data engineering, analytics, automation, AI/ML, or related technical roles. Experience designing and developing scalable data pipelines…

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