Commercial Data & AI Lead

# Commercial Data & AI Lead

Embedded in Greater Customer Teams (GCTs), the Commercial Data & AI Lead is a commercially driven technologist who bridges proposition strategy and customer execution. You translate customer challenges into compelling, standardized data and AI solutions, accelerate sales cycles through technical expertise, and ensure that what we propose is both desirable for customers and feasible for our delivery teams.

## Key Responsibilities

Opportunity Qualification & Sales Enablement

• Identify and qualify cross-sell and upsell opportunities within existing customer accounts
• Support customer teams in early-stage sales conversations by understanding customer data and AI challenges
• Match customer needs to standard services and reusable digital assets (RDAs)
• Act as the proposition expert ensuring data and AI services portfolio is positioned effectively

Solution Design & Proposal Development

• Co-create solution designs with team tech leads that maximize standardization
• Support RfP responses, deliver demos, reference architectures, and technical deep-dives
• Provide trusted advisory on deal structure, scoping, and pricing

Proposition Product Management & Feedback

• Work closely with Data & AI Ambassador on proposition roadmaps and positioning
• Provide structured feedback from customer engagements including win/loss analysis
• Spot opportunities to create new reusable data and AI assets

Customer Engagement & Technical Consulting

• Serve as trusted technical advisor discussing data architectures, AI/ML platforms, analytics pipelines
• Quantify value and explain trade-offs through demos, proof-of-concepts, and workshops
• Build credibility with both technical and executive stakeholders

Standardization & Continuous Improvement

• Create standard templates, checklists, and reusable sales enablement materials
• Champion use of data platform strategy and productized services
• Ensure consistency and scale across engagements

## Required Profile

You are primarily commercially driven but with a strong data engineering or AI foundation. You understand data architectures and AI/ML systems, can quantify business value, and know how to structure data and AI engagements. You excel at simplifying complex topics, building trust quickly, and telling a coherent proposition story that resonates with technical and non-technical audiences alike.

Technology (3-5 years of experience):

• Hands-on experience in data engineering