Senior Data Scientist - Supply Chain Operations

hackajob is collaborating with Oracle to connect them with exceptional professionals for this role. Description Oracle Cloud Infrastructure (OCI) is seeking a highly motivated Sr. Data Scientist – Supply Chain to help accelerate the digital transformation of OCI's global supply chain operations. Reporting to the Senior Director of Data Automation, Supply Chain, this role will design, develop, and implement advanced data platforms, AI-enabled automation, predictive analytics, and operational intelligence solutions that improve efficiency, scalability, and decision-making across OCI's rapidly growing supply chain organization. As a senior individual contributor, you will partner closely with Supply Planning, Manufacturing, Sourcing, Logistics, Capacity Planning, Data Center Operations, and Engineering teams to develop intelligent automation, operational dashboards, machine learning models, and data products that enable proactive management of supply chain operations. This role requires deep technical expertise, strong business acumen, and the ability to influence cross-functional stakeholders through data-driven solutions. 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 Experience 3-5 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. Qualifications Minimum Job Qualifications Education and/or Experience: 8 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 4 years of experience in data science, machine learning, data engineering, or related field OR Master's Degree in Data Science, Mathematics, Statistics, Computer Science, Machine Learning, Bioinformatics, Mathematical Finances, Information Systems, Operations Research, Economics, Physics, or related field AND 2 years of experience in data science, machine learning, data engineering, or related field OR Doctorate in Data Science, Mathematics, Statistics, Computer Science, Machine Learning, Bioinformatics, Mathematical Finances, Information Systems, Operations Research, Economics, Physics, or related field. Job Skills: Same skills as prior level plus Data Management Demonstrated ability in or knowledge of data management, including designing, operationalizing, securing, and monitoring data pipelines. Preferred Job Qualifications Education and/or Experience: 9 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 5 years of experience in data science, machine learning, data engineering, or related field OR Master's Degree in Data Science, Mathematics, Statistics, Computer Science, Machine Learning, Bioinformatics, Mathematical Finances, Information Systems, Operations Research, Economics, Physics, or related field AND 3 years of experience in data science, machine learning, data engineering, or related field OR Doctorate in Data Science, Mathematics, Statistics, Computer Science, Machine Learning, Bioinformatics, Mathematical Finances, Information Systems, Operations Research, Economics, Physics, or related field AND 1 year of experience in data science, machine learning, data engineering, or related field. Job Skills: Same skills as prior level plus; Generative Artificial Intelligence (GenAI) Model Building Demonstrated ability in or knowledge of GenAI model building, including training, fine-tuning, and monitoring generative AI solutions. Innovation Demonstrated ability in or knowledge of innovation, including generating or supporting new ideas, technologies, or processes for organizational growth. Production Grade Software: 1 year of experience in contributing to the development of production grade software.aa415a4b-8b21-40fc-a65c-70d2b25ca29a