Furniture Industries is seeking a Supply Chain Analytics Manager to lead the data and analytics agenda for our Supply Chain function from the Vietnam Global Capability Center (GCC). This strategic, hands-on leadership role calls for someone who combines deep expertise in AI/ML, data engineering, and data management with strong supply chain domain knowledge, and who can turn data into a competitive advantage across our end-to-end supply chain.
Key Highlights
· Build a unified, AI-ready supply chain data foundation and semantic model for the entire SC team
· Drive process automation and insight-led, financially grounded decision-making
· Partner with global IT on data integrity, governance, and architecture
· Serve as a strategic analytics partner to senior supply chain leadership
· Lead and develop a high-performing data and analytics team
ESSENTIAL DUTIES & RESPONSIBILITIES
- Build a Unified Supply Chain Data Foundation and Semantic Layer: Architect and establish a centralized supply chain data pool built on a robust semantic model that serves the entire SC team as a single source of truth. Design the semantic layer to standardize business definitions, metrics, and hierarchies across demand, supply, procurement, manufacturing, inventory, and logistics. Position this foundation to power next-generation AI-driven analytics and self-service/conversational reporting, progressively replacing traditional static Power BI dashboards with scalable, query-ready and AI-ready data products.
- Drive Process Automation and Insight-Led Decision Making: Lead the team to identify, design, and deploy automation solutions that reduce manual effort and support business team workflows across planning, procurement, and operations. Move the function beyond descriptive reporting toward predictive and prescriptive analytics that generate actionable insights. Embed financial analysis into supply chain decisions—linking operational metrics to cost, margin, working capital, and ROI—so that recommendations are quantified in business and financial terms and directly support decision-making.
- Partner with Global IT to Ensure Data Integrity and Architecture: Work closely with the global IT organization to align enterprise data architecture, integration standards, and platform strategy. Ensure data integrity, consistency, security, and governance across source systems (ERP, SCM, and related platforms). Collaborate on data pipelines, master data management, and architectural decisions so that the SC analytics environment is scalable, well-governed, and aligned with global standards and the broader technology roadmap.
- Serve as a Strategic Analytics Partner to SC Senior Leadership: Act as a trusted partner to the senior supply chain leadership team, anticipating their data and analytics needs and translating strategic priorities into analytical solutions. Deliver timely, accurate data support, performance insights, and scenario analyses that inform planning and strategy. Build analytics capabilities that elevate leadership's visibility into supply chain performance and enable data-driven, proactive decision-making at the executive level.
- Lead, Develop, and Guide the Analytics Team: Lead, mentor, and grow a high-performing team of analysts and data professionals. Set clear goals, provide technical guidance across AI/ML, data engineering, and analytics, and foster a culture of continuous learning, collaboration, and accountability. Manage workload prioritization, professional development, and delivery quality, while developing the team's domain expertise in supply chain and their capabilities in modern data and AI tooling.ng best practices in data management, advanced analytics, and data visualization.
MINIMUM QUALIFICATIONS
Education
- Bachelor's or Master's in Supply Chain, Industrial Engineering, Computer Science, Data Science, Statistics, Operations Research, or related field – Required.
Experience
- 7+ years in supply chain analytics – Required.
- 3+ years in a managerial or team-lead capacity, ideally within manufacturing, retail – Required.
Knowledge, Skills, and Abilities
- AI / Machine Learning: Hands-on experience building and deploying ML models for supply chain use cases such as demand forecasting, inventory optimization, lead-time prediction, supplier risk scoring, and logistics optimization. Proficiency with frameworks like scikit-learn, TensorFlow, PyTorch, and XGBoost. Familiarity with time-series forecasting (ARIMA, Prophet, LSTM) and optimization techniques (linear/mixed-integer programming, heuristics). Exposure to GenAI/LLM applications for supply chain is a plus.
- Data Engineering: Strong skills in building and maintaining data pipelines (ETL/ELT), data modeling, and warehousing. Ability to design scalable architectures handling large, multi-source supply chain datasets.
- Data Management: Solid grasp of data governance, data quality, master data management (especially supplier, SKU, and inventory master data), and metadata management.
- Technical Stack: Advanced SQL and Python (or R). Proficiency with BI/visualization tools (Power BI, Tableau, or Looker). Experience integrating analytics with ERP and SCM systems (SAP, Oracle, or equivalent).
- Supply Chain Domain Knowledge: Deep understanding of end-to-end supply chain processes: demand planning, S&OP, procurement, manufacturing, inventory management, warehousing, and logistics/transportation. Familiarity with KPIs such as forecast accuracy, fill rate, OTIF, inventory turns, and landed cost.
- Leadership and Soft Skills: Proven ability to lead and develop analytics teams, manage stakeholders across global and regional functions, and translate business problems into analytical solutions. Strong communication skills to present insights to non-technical leadership. Experience working in a Global Capability Center (GCC) or shared-services model collaborating with overseas headquarters is highly valued.
- Other: English fluency, project management familiarity (Agile/Scrum) is a plus.
