Principal Data Scientist – Supply Chain Operations

About the Role

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.

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.

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, analytics platforms, and automation solutions.
• Proven experience delivering data products and dashboards supporting cross-functional business operations.
• Experience applying predictive analytics or machine learning to solve operational or supply chain challenges.
• Demonstrated ability to independently lead complex technical initiatives from concept through implementation.
• Experience supporting supply chain, manufacturing, logistics, procurement, or cloud infrastructure operations is preferred.

Technical Skills

• Strong proficiency in SQL and Python for data engineering, automation, and analytics.
• Experience with ETL/ELT pipelines, data modeling, orchestration frameworks, and cloud-based data platforms.
• Knowledge of AI/ML techniques, predictive analytics, and automation frameworks.
• Experience with business intelligence and visualization tools such as Oracle Analytics Cloud, Tableau, or Power BI.
• Familiarity with Oracle Fusion Cloud Applications (SCM, Procurement, Planning, ERP) is preferred.
• Understanding of forecasting, inventory management, manufacturing operations, logistics, and supply planning concepts.
• Experience working with cloud technologies and distributed systems architectures is a plus.

Professional Skills

• Strong analytical and problem-solving abilities with attention to detail.
• Excellent communication skills with the ability to explain technical concepts to both technical and business audiences.
• Ability to manage multiple priorities in a fast-paced, rapidly evolving environment.
• Demonstrated ability to influence stakeholders and drive technical solutions without direct managerial authority.
• Self-motivated with a passion for automation, continuous improvement, and innovation.

Education and Experience

Minimum: 11 years of experience in data science, machine learning, data engineering, or related field OR Bachelor's Degree in Data Science, Mathematics, Statistics, Computer Science, Machine Learning, Bioinformatics, Mathematical Finances, Information Systems, Operations Research, Economics, Physics, or related field AND 7 years of experience OR Master's Degree in aforementioned fields AND 5 years of experience OR Doctorate in aforementioned fields AND 3 years of experience.

Job Skills: Automation – demonstrated ability in or knowledge of designing, implementing, and managing automated tools, processes, or systems. Code Review – demonstrated ability to conduct in-depth code reviews for software quality assurance. Troubleshooting – demonstrated ability in or knowledge of diagnosing and resolving issues across various technical domains. Production Grade Software: 2 years of experience in contributing to or leading the development of production grade software.

Preferred: 12 years of experience OR Bachelor's Degree AND 8 years OR Master's AND 6 years OR Doctorate AND 4 years. Generative Artificial Intelligence (GenAI) Model Building – demonstrated ability in or knowledge of training, fine-tuning, and monitoring generative AI solutions. Innovation – demonstrated ability in or knowledge of generating or supporting new ideas, technologies, or processes for organizational growth.