AI / Data Business Analyst – Strategy, Problem Solving & Analytics | Global Truck
The AI/Data Business Analyst will translate market, customer and operational data into actionable insights to drive profit improvements for the T6 vehicle programme. They will design and implement AI‑driven analytics and automation solutions that accelerate decision‑making and streamline cross‑functional workflows.
Skills required
About this role
We are looking for an AI / Data Business Analyst to accelerate the practical use of AI, advanced analytics and intelligent automation across the T6 vehicle programme.
The role will turn complex market, customer, competitor, commercial and operational data into clear, evidence-based decisions, scenarios and actions, shortening the path from data to action.
Combining commercial judgement, structured problem-solving and hands-on AI capability, the specialist will support the T6 Director and cross-functional teams with clear insights, profit improvement opportunities and more efficient workflows.
This is a hands-on business role, not reporting or technology theory. Success means faster, clearer decisions, reduced delivery friction and measurable business outcomes.
Responsibilities
AI Strategy, Agents & Intelligent Automation
Identify high-value business problems where AI can remove low-value information processing, improve decision quality, reduce time to clarity or create a new capability.
Design, prototype and improve AI agents and assistants that interrogate approved documents, data, dashboards, meeting records and other enterprise information sources.
Create repeatable workflows for evidence extraction, anomaly detection, scenario evaluation, summarisation, decision preparation and action tracking.
Advanced Analytics & Decision Intelligence
Analyse relevant 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 that concentrate attention on material issues.
Run sensitivity and counterfactual analyses where appropriate to show how recommendations change as key assumptions, market conditions or programme constraints move.
Time to Clarity / Delivery Acceleration
Take information-heavy business questions and rapidly define the material evidence and minimum information required to move forward.
Use bottom-line-up-front synthesis so leaders can understand the reality, what is missing, and what would change the recommendation, value or risk through the full analytical trail.
Convert analysis into an executable next step with owners. Creating reusable decision tools, and workflows that reduce repeated analysis and improve consistency across recurring reviews.
Track whether the intervention shortened decision or delivery cycle time, reduced rework, closed evidence gaps or improved execution reliability.
Competitive, Market & Customer Intelligence
Create and maintain evidence-led competitor comparisons covering product, price, customer and markets.
Identify meaningful market patterns while challenging groupings that do not materially alter the decision.
Convert technical measures and user evidence into customer, operator and business outcomes that support programme, marketing, sales and communications decisions.
AI Capability, Adoption & Governance
Act as a focal point for practical AI application, use-case discovery and solution reuse within T6 organisation.
Support safe adoption within approved enterprise platforms and proportionate controls for sensitive data, business-critical outputs and reusable automation.
Cross-Functional & Global Business Integration
Work across functions and relevant markets, connecting product, programme, market, customer, competitor, financial and operational intelligence.
Share analytical tools, evidence standards and best practices across geographically dispersed teams.
Influence cross-functional stakeholders without relying on formal authority and maintain momentum through clear ownership and follow-up.
Qualifications
Minimum QualificationsBachelor'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.
Experience in automotive product development, programme management, product planning, strategy, finance, marketing, sales, research, defence or commercial operations.
Hands-on experience developing AI agents, enterprise assistants, Generative AI solutions or automated business workflows.
Experience with Microsoft 365 Copilot, Copilot agents, Ford-approved LLM platforms, Power BI, Power Automate or comparable tools.
Experience with Six Sigma, Black Belt, human-centred design or comparable structured problem-solving methods and analytical dashboards.
Time to clarity / Delivery acceleration: Turn ambiguity and information overload into a decision-ready evidence position quickly, without hiding uncertainty and shorten the path from decision to execution.
Think strategically: Move from data to insight, recommendation, decision and action with a clear focus on business results
Build, not just use, AI: Create practical agents, workflows, decision tools and reusable methods.
Evidence discipline: Know what is verified, assumed, missing and what proof would reverse the recommendation.
Constructive challenge: Expose contradictions, weak dependencies and KPI conflicts without creating unproductive friction.
