Job Description

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

Supply Chain Data Analytics & Business Intelligence Specialist III

The Supply Chain Data Analytics & Business Intelligence Specialist III serves as a key analytical and digital transformation partner within the supply chain organization. This role is responsible for developing scalable data solutions, business intelligence tools, automated reporting capabilities, and AI-enabled insights that improve supply chain visibility, supplier performance, forecast alignment, risk management, and operational efficiency.

This position focuses on transforming complex supply chain data into actionable insights that support proactive decision-making across planning, procurement, operations, sourcing, and supplier management teams. The specialist will leverage advanced analytics, data visualization, process automation, artificial intelligence, and digital tools to streamline manual processes, improve data accuracy, enhance performance tracking, and identify opportunities for continuous improvement.

The role requires strong technical capability in data analytics tools such as SQL, R, Power BI, Excel, and other business intelligence platforms, as well as practical experience using automation and AI-enabled tools, including coding assistants or automation platforms such as Codex or similar technologies. The specialist will act as a bridge between supply chain stakeholders, analytics teams, digital teams, IT, and business leaders to deliver data-driven solutions that improve supply chain performance and decision quality.

Key Responsibilities

Supply Chain Analytics & Business Intelligence

• Design, develop, maintain, and enhance supply chain dashboards, scorecards, automated reports, and analytical tools to provide visibility into key performance metrics.
• Translate business requirements into scalable data models, reporting solutions, and actionable insights for supply chain stakeholders.
• Analyze large and complex datasets related to supplier performance, forecast accuracy, inventory, delivery performance, service levels, supply risks, and operational efficiency.
• Use SQL, R, Power BI, Excel, and other analytical tools to extract, transform, model, analyze, and visualize supply chain data.
• Develop standard KPIs, metrics definitions, and reporting logic to ensure consistent performance measurement across teams and divisions.
• Identify data gaps, process inconsistencies, reporting inefficiencies, and opportunities to improve data quality and analytical capabilities.
• Provide business insights and recommendations to support strategic sourcing, procurement, planning, supplier management, and operational decision-making.

Process Automation & Digital Transformation

• Identify, evaluate, and implement automation opportunities to reduce manual work, improve reporting accuracy, shorten cycle times, and increase process efficiency.
• Develop automated workflows, scripts, reporting pipelines, and digital tools to streamline repetitive supply chain processes.
• Leverage automation tools, coding assistants, and AI-enabled technologies such as Codex or similar platforms to accelerate solution development and improve productivity.
• Partner with Digital, IT, Analytics, and business teams to deploy scalable automation and business intelligence solutions.
• Support digital transformation initiatives across supply chain by improving data visibility, standardizing reporting processes, and enabling self-service analytics.
• Continuously assess existing manual processes and recommend improved ways of working through data, automation, and technology.
• Promote adoption of digital tools and analytical solutions through training, documentation, stakeholder engagement, and change management.

Artificial Intelligence & Advanced Analytics

• Apply AI-enabled tools and advanced analytics to support predictive insights, exception management, forecasting improvement, supplier risk identification, and operational decision support.
• Explore and implement use cases for artificial intelligence in supply chain analytics, reporting automation, root cause analysis, and performance monitoring.
• Use AI tools responsibly to accelerate data analysis, generate insights, automate documentation, improve decision support, and enhance productivity.
• Partner with cross-functional teams to identify practical AI opportunities that improve supply chain efficiency, responsiveness, and business outcomes.
• Support the development of predictive or prescriptive analytics capabilities to anticipate risks, constraints, performance issues, and improvement opportunities.
• Stay current on emerging analytics, automation, and AI technologies that can be applied to supply chain processes.

Supplier Performance & Operational Insights

• Develop and maintain supplier performance dashboards covering key metrics such as delivery performance, forecast accuracy, service level, responsiveness, and risk indicators.
• Analyze supplier performance trends to identify root causes, recurring issues, risks, and opportunities for improvement.
• Provide data-driven insights to support supplier business reviews, performance discussions, corrective actions, and continuous improvement initiatives.
• Monitor supplier health, risk exposure, capacity signals, and performance exceptions through automated dashboards and analytical models.
• Support supplier performance governance by ensuring accurate, timely, and transparent reporting of supplier metrics and improvement actions.
• Collaborate with Procurement, Planning, Sourcing, Operations, and Supplier Management teams to align insights with business priorities.

Forecast, Demand & Supply Visibility

• Support forecast consolidation, demand alignment, and supply planning processes through analytical tools, dashboards, and data-driven insights.
• Analyze forecast accuracy, forecast adherence, supplier capacity signals, and potential supply constraints.
• Build reporting tools that improve visibility into forecast changes, demand trends, supplier outlooks, capacity gaps, and escalation risks.
• Support Sales & Operations Planning, supply planning, and supplier collaboration processes by providing clear and actionable analytical recommendations.
• Identify opportunities to improve forecast visibility and decision-making through automation, analytics, and standardized reporting.

Data Governance & Continuous Improvement

• Validate data accuracy, troubleshoot system or reporting issues, and ensure reliable business intelligence outputs.
• Partner with data owners and business stakeholders to improve data governance, reporting consistency, and metric standardization.
• Document reporting logic, data sources, automation workflows, and analytical methodologies.
• Lead or support continuous improvement projects focused on process efficiency, data quality, business visibility, and analytical maturity.
• Communicate insights, risks, opportunities, and recommendations clearly to technical and non-technical audiences.
• Share best practices, support onboarding activities, and promote a culture of continuous improvement, digital adoption, and data-driven decision-making.

Qualifications

• Bachelor’s or master’s degree in Supply Chain, Engineering, Business Analytics, Data Science, Information Systems, Operations Management, Industrial Engineering, or related field.
• 4+ years of experience in supply chain analytics, business intelligence, supplier performance, supply planning, procurement analytics, operations analytics, or related functions.
• Strong proficiency in SQL for data extraction, transformation, querying, and analysis.
• Experience using Phyton for statistical analysis, data modeling, automation, or advanced analytics strongly preferred.
• Strong proficiency with Power BI, Tableau, or similar data visualization and business intelligence tools.
• Advanced Excel skills, including complex formulas, pivot tables, Power Query, data modeling, and automation capabilities.
• Experience developing dashboards, scorecards, automated reports, KPIs, and executive-level performance insights.
• Experience with process automation, scripting, workflow automation, or low-code/no-code automation tools.
• Familiarity with AI-enabled tools, coding assistants, or automation platforms such as Codex, ChatGPT, Copilot, or similar technologies.
• Experience applying AI, machine learning, predictive analytics, or advanced analytics to supply chain or operational business problems preferred.
• Knowledge of supply chain processes, including planning, procurement, supplier management, inventory, logistics, forecasting, and S&OP.
• Experience with SAP, ERP systems, data warehouses, or enterprise reporting environments preferred.
• Ability to translate business needs into analytical solutions and communicate insights effectively to cross-functional stakeholders.
• Strong problem-solving skills with the ability to work with ambiguous data, complex processes, and multiple stakeholder groups.
• Proven ability to manage priorities, lead improvement initiatives, and influence change across cross-functional teams.
• Excellent communication, presentation, facilitation, and stakeholder management skills.
• Professional certifications such as CSCP, CPIM, Lean Six Sigma, Power BI, Data Analytics, or related certifications are highly desirable.

Competencies

• Supply Chain Data Analytics
• Business Intelligence & Data Visualization
• SQL, R & Advanced Data Tools
• Artificial Intelligence Enablement
• Process Automation & Digital Transformation
• Data-Driven Problem Solving
• Supplier Performance Analytics
• Forecasting & Supply Planning Insights
• KPI Development & Performance Management
• Data Governance & Reporting Standardization
• Continuous Improvement Leadership
• Cross-Functional Collaboration
• Change Management & Digital Adoption
• Executive Communication & Storytelling with Data
• Strategic Thinking & Decision Quality
• Operational Excellence