Women in Aviation International

Supply Chain

• Own the design and improvement of analytical tools, planning workflows, dashboards, and system-enabled processes that support demand, supply, inventory, and operations decisions.
• Build predictive, prescriptive, and optimization models for forecasting, inventory risk, supply constraints, service performance, and exception detection using AI, automation, and self-service solutions to drive decision quality and speed.
• Perform exploratory analysis, root-cause analysis, data validation, feature development, and performance measurement to support business solutions.
• Develop scenario and simulation models to quantify tradeoffs across service, cost, inventory, and risk.
• Translate supply chain and business problems into scalable analytical solutions embedded in processes and systems.
• Partner with IT, planning, operations, and finance teams to improve data flows, reporting structures, planning system outputs, and analytical tools used throughout our planning processes.
• Clearly communicate findings to technical and non-technical stakeholders through visualizations, recommendations, and business insights.
• Improve data quality, metric consistency, and analytical rigor across the planning organization.

Senior Analyst, Global Supply Chain Planning

• Own the design and improvement of analytical tools, planning workflows, dashboards, and system-enabled processes that support demand, supply, inventory, and operations decisions
• Build predictive, prescriptive, and optimization models for forecasting, inventory risk, supply constraints, service performance, and exception detection using AI, automation, and self-service solutions to drive decision quality and speed
• Perform exploratory analysis, root-cause analysis, data validation, feature development, and performance measurement to support business solutions
• Develop scenario and simulation models to quantify tradeoffs across service, cost, inventory, and risk
• Translate supply chain and business problems into scalable analytical solutions embedded in processes and systems
• Partner with IT, planning, operations, and finance teams to improve data flows, reporting structures, planning system outputs, and analytical tools used throughout our planning processes
• Clearly communicate findings to technical and non-technical stakeholders through visualizations, recommendations, and business insights
• Improve data quality, metric consistency, and analytical rigor across the planning organization.

AI Engineer

• Lead the design, build, deployment, and continuous improvement of WAI's AI-ready data and platform foundation across sales, inventory, planning, catalog, customer, order, product, and related business systems.
• Design, build, and govern a centralized data lake that consolidates critical data from ERP and other core business systems into a single trusted foundation, enabling AI tools, models, and analytics to reliably access enterprise data.
• Identify repetitive and manual tasks, use process mining to uncover workflow bottlenecks, and implement RPA solutions to improve efficiency and streamline operations.
• Own technical architecture for AI/ML/LLM workflows, RAG, embeddings, vector search, structured data query, dashboards, APIs, model serving, and monitoring.
• Connect, ingest, clean, validate, normalize, and automate data pipelines from structured and unstructured sources, including enterprise systems, reports, documents, PDFs, spreadsheets, and business notes.

Director, AI Platform and Development Engineering

• Build and support AI-ready access to WAI catalog, customer, order, product, sales-channel, and related business data as directed by AI platform leadership.
• Assist with Infor integration and other trusted data connections so AI outputs are grounded in approved business data sources.
• Implement semantic, keyword, and structured search across catalog, OE number, fitment, cross-reference, technical specification, and product data.
• Parse and structure PDFs, Excel files, fitment guides, manufacturer specifications, RMA forms, customer questions, chatbot conversations, and other technical or business documents.
• Build and support retrieval-augmented generation (RAG), embeddings, vector search, document ingestion pipelines, prompt workflows, and AI assistant capabilities for internal users and distributor support.
• Capture and organize real user questions, failed searches, corrections, successful answers, and feedback to support evaluation data, retrieval improvement, and future model tuning.
• Assist with evaluating, deploying, and testing approved hosted or open-source models such as Llama, Mistral, Qwen, or similar models under technical direction.
• Support AI workflows related to Amazon Business trends, listing performance, returns, customer demand, and other approved business intelligence use cases as assigned.
• Document technical logic, data mappings, prompts, retrieval sources, test cases, known issues, and support procedures.
• Test AI outputs for source grounding, accuracy, consistency, reliability, and alignment with acceptance criteria.
• Monitor assigned workflows, troubleshoot defects, analyze failures, and recommend improvements to retrieval quality, data quality, model behavior, and workflow performance.
• Collaborate with offshore and onsite team members, IT, data owners, and business-facing AI resources to deliver approved work within WAI standards.
• Undertakes additional responsibilities and tasks as directed by management.

Analyst, AI Engineer

Product Manager

• Implement product strategy and develop product platforms to ensure maximum application coverage and revenue using available data sources aligned with market needs for quality, pricing, features, and benefits.
• Conduct OE part number research and prioritize high-potential applications for product expansion.
• Identify sourcing partners and collaborate with sourcing teams to validate sourced parts.
• Partner with MDM and item release teams to establish and maintain new part information.
• Participate in quality assurance and validation testing for product line parts.
• Collaborate with catalog teams to develop product coverage reports and customer communications.
• Conduct periodic business reviews and manage key revenue, coverage, and margin KPIs.
• Maintain an understanding of prevailing market trends within related product categories.