AI / Data Business Analyst – Strategy, Problem Solving, Analytics

Ford Motor Company

. Identify high-value business problems where AI can reduce low-value information processing, improve decision quality, reduce time to clarity or create new capabilities.

Posted 10/27/2026full-timeBangkok • ThailandMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Generative AI, AI assistants, and analytical workflows, with a strong ability to synthesize complex data into actionable insights and decision tools. Proficient in Microsoft Excel and PowerPoint for analytical modeling and executive storytelling, while effectively influencing cross-functional stakeholders.

Highest-signal resume keywords

Generative AIAnalytical ModellingMicrosoft ExcelAI-Enabled Analytical WorkflowsDecision Tools

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Analytical ModellingEvidence ExtractionAnomaly DetectionScenario EvaluationDecision PreparationAction TrackingSensitivity AnalysisCounterfactual AnalysisData AnalysisMarket Analysis

Soft Skills

Written CommunicationVerbal CommunicationInfluencing StakeholdersIndependent OperationProblem-Solving

Tools & Technologies

Microsoft 365 CopilotPower BIPower AutomateFord-Approved LLM PlatformsAI Agents

Certifications & Qualifications

Six SigmaBlack Belt

Industry Keywords

Automotive Product DevelopmentProgramme ManagementProduct PlanningFinanceMarketingSalesResearchDefenceCommercial Operations

About the role

Key responsibilities & impact

Identify high-value business problems where AI can reduce low-value information processing, improve decision quality, reduce time to clarity or create new capabilities.
Design, prototype and improve AI agents and assistants using approved enterprise information sources.
Create repeatable workflows for evidence extraction, anomaly detection, scenario evaluation, summarisation, decision preparation and action tracking.
Analyse vehicle programme, product, sales, share, pricing, incentives, contribution margin, cost, quality, market, customer, competitor and operational data.
Build analytical models, scenario views, reports and dashboards focused on material issues.
Run sensitivity and counterfactual analyses to show how recommendations change with assumptions, market conditions or programme constraints.
Define material evidence and minimum information needed to address information-heavy business questions.
Synthesise findings for leaders, showing reality, missing information and factors that could change recommendations, value or risk.
Convert analysis into executable next steps with owners and create reusable decision tools and workflows.
Track decision and delivery cycle time, rework, evidence gaps and execution reliability.
Create and maintain evidence-led competitor comparisons covering product, price, customer and markets.
Identify meaningful market patterns and challenge groupings that do not materially alter decisions.
Translate technical measures and user evidence into customer, operator and business outcomes supporting programme, marketing, sales and communications decisions.
Act as a focal point for practical AI application, use-case discovery and solution reuse within the T6 organisation.
Support safe AI adoption within approved enterprise platforms and proportionate controls.
Connect product, programme, market, customer, competitor, financial and operational intelligence across functions and markets.
Share analytical tools, evidence standards and best practices across geographically dispersed teams.
Influence cross-functional stakeholders without formal authority and maintain momentum through ownership and follow-up.

Requirements

What you’ll need

Bachelor's degree or equivalent professional experience in Business, Engineering, Economics, Finance, Computer Science, Data Analytics, Marketing or a related discipline.
Strong practical understanding of Generative AI, AI assistants or agents, prompt/context design and AI-enabled analytical workflows.
Advanced competence in Microsoft Excel and PowerPoint, including analytical modelling and executive-level visual storytelling.
Strong written and verbal communication for senior-management audiences, with the ability to operate independently across competing priorities.
Preferred: experience in automotive product development, programme management, product planning, strategy, finance, marketing, sales, research, defence or commercial operations.
Preferred: hands-on experience developing AI agents, enterprise assistants, Generative AI solutions or automated business workflows.
Preferred: experience with Microsoft 365 Copilot, Copilot agents, Ford-approved LLM platforms, Power BI, Power Automate or comparable tools.
Preferred: experience with Six Sigma, Black Belt, human-centred design or comparable structured problem-solving methods and analytical dashboards.
Ability to turn ambiguity and information overload into a decision-ready evidence position quickly without hiding uncertainty.
Ability to move from data to insight, recommendation, decision and action with a clear focus on business results.
Ability to create practical agents, workflows, decision tools and reusable methods.
Ability to distinguish verified, assumed and missing evidence and identify what proof would reverse a recommendation.
Ability to expose contradictions, weak dependencies and KPI conflicts constructively.