Principal Data Scientist - Supply Chain

Salary: $142,000 - 194,000 per year Requirements:

• We require 7-10+ years of experience in data engineering, analytics, automation, AI/ML, or a related technical discipline.
• We need experience designing and delivering scalable data pipelines, analytics platforms, and automation solutions.
• We look for a track record of producing data products and dashboards that support cross-functional business operations.
• We require experience applying predictive analytics or machine learning to operational or supply chain challenges.
• We need the ability to independently lead complex technical initiatives from concept to implementation.
• Experience supporting supply chain, manufacturing, logistics, procurement, or cloud infrastructure operations is preferred.
• Strong SQL and Python skills for data engineering, automation, and analytics are required.
• We expect experience with ETL/ELT pipelines, data modeling, orchestration frameworks, and cloud-based data platforms.
• Knowledge of AI/ML methods, predictive analytics, and automation frameworks is required.
• Experience with business intelligence and visualization tools such as Oracle Analytics Cloud, Tableau, or Power BI is expected.
• Familiarity with Oracle Fusion Cloud Applications, including SCM, Procurement, Planning, and ERP, is preferred.
• We look for understanding of forecasting, inventory management, manufacturing operations, logistics, and supply planning concepts.
• Experience working with cloud technologies and distributed system architectures is a plus.
• Strong analytical and problem-solving skills with close attention to detail are required.
• Excellent communication skills and the ability to explain technical concepts to technical and non-technical audiences are required.
• We need the ability to manage multiple priorities in a fast-paced, evolving environment.
• Demonstrated ability to influence stakeholders and drive technical solutions without direct managerial authority is required.
• A self-motivated mindset with a passion for automation, continuous improvement, and innovation is expected.
• We require either 11 years of experience in data science, machine learning, data engineering, or a related field, or a Bachelors degree in a relevant field plus 7 years of experience, or a Masters degree plus 5 years of experience, or a Doctorate plus 3 years of experience.
• We require demonstrated ability in automation, including designing, implementing, and managing automated tools, processes, or systems.
• We require demonstrated ability to conduct in-depth code reviews for software quality assurance.
• We require demonstrated ability in troubleshooting and resolving issues across technical domains.
• We require 2 years of experience contributing to or leading the development of production-grade software.
• Preferred qualifications include 12 years of experience in data science, machine learning, data engineering, or a related field, or a Bachelors degree plus 8 years of experience, or a Masters degree plus 6 years of experience, or a Doctorate plus 4 years of experience.
• Preferred skills include GenAI model building, including training, fine-tuning, and monitoring generative AI solutions.
• Preferred skills also include innovation, including generating or supporting new ideas, technologies, or processes for organizational growth.

• We design, build, and maintain scalable data automation solutions that support OCIs global supply chain.
• We develop AI and machine learning models to improve forecasting, inventory optimization, supply planning, logistics execution, manufacturing readiness, and operational performance.
• We identify opportunities to reduce manual work through automation, predictive analytics, and intelligent workflows.
• We create reusable automation frameworks and data products that enhance operational efficiency and scalability.
• We evaluate emerging AI and automation technologies and recommend practical uses across supply chain operations.
• We design and develop robust data pipelines, models, and architectures that support real-time operational reporting and advanced analytics.
• We build scalable datasets for forecasting, planning, inventory management, supplier performance, and deployment execution.
• We ensure data quality, governance, reliability, and accessibility across multiple enterprise systems.
• We develop dashboards, scorecards, and self-service analytics that improve visibility across global supply chain functions.
• We collaborate with engineering teams to integrate data across Oracle Fusion Cloud Applications, operational systems, and cloud platforms.
• We develop operational dashboards, KPI frameworks, and control tower capabilities that provide end-to-end supply chain visibility.
• We create intelligent alerting mechanisms that proactively surface operational risks, exceptions, and bottlenecks.
• We build predictive models that support scenario planning, capacity management, supplier performance, and deployment readiness.
• We translate complex operational data into actionable insights for both day-to-day execution and long-term planning.
• We partner with Supply Planning, Procurement, Manufacturing, Logistics, Capacity Management, and Data Center Operations teams to understand business challenges and develop scalable technical solutions.
• We collaborate with product managers, engineers, and business stakeholders to define analytics requirements and deliver impactful data solutions.
• We provide technical guidance and subject matter expertise for automation initiatives and enterprise data projects.
• We help shape best practices for data engineering, analytics, and automation across the organization.
• We drive improvements in data quality, automation, reporting accuracy, and operational efficiency.
• We identify opportunities to simplify processes, reduce technical debt, and improve data platform maintainability.
• We document technical designs, data models, and automation solutions to support long-term scalability and operational excellence.
• We stay current with emerging technologies in AI, machine learning, cloud computing, and data engineering.

• AI
• Architect
• Business Intelligence
• Cloud
• ETL
• ERP
• Fine-tuning
• Support
• Machine Learning
• Oracle
• Power BI
• Python
• SQL
• Tableau
• Security

More:

hackajob is collaborating with Oracle to connect them with exceptional professionals for this role. We use advanced experimental design, statistics, and technologies such as machine learning and natural language processing to uncover data patterns and trends that generate actionable insights for client services, product enhancement, and business impact. We train, deploy, and monitor machine learning models, architect solutions across the full model lifecycle, optimize prompts, summarize and interpret data findings, and implement ETL for secure data pipelines. The role focuses on efficient, scalable code and staying current with developments in data science.

last updated 37 week of 2026