Gerente Senior de Transformación en IA y Analítica Avanzada

The Head of AI Transformation & Advanced Analytics will lead CWP's enterprise-wide adoption of AI, advanced analytics and intelligent automation, turning them into a sustained source of competitive advantage and measurable EBITDA impact. Reporting to the Chief Strategy Officer, the role owns the AI transformation roadmap, the underlying solution architecture, and the analytics products that support commercial, network, customer experience and operational decisions across the company.

Working in close partnership with the Heads of Strategy & New Business and BI & Data Engineering, the role is accountable for translating business priorities into a portfolio of AI and analytics use cases, designing the operating model and target architecture, and ensuring delivery, adoption and value capture in the front line.

 

 

 

Strategy & roadmap

• Define and own the AI transformation strategy and multi-year roadmap for CWP, aligned with the corporate strategy, the LLA group agenda and the priorities of commercial, network, customer operations and finance.
• Build and continuously prioritize the portfolio of AI, GenAI and advanced analytics use cases — including business case, expected value, dependencies, risk and time-to-value — and present it to the Executive Committee.
• Establish AI governance, ethics, model-risk and responsible-AI standards in coordination with Legal, Risk, Cybersecurity and Data Privacy.

Process & workflow design

• Lead the Process/Workflow Designer Managers in re-engineering end-to-end customer and operational journeys (sales, care, fulfillment, assurance, billing/collections, retention) so they are AI-native and automation-ready.
• Define target operating models and human-in-the-loop designs that combine intelligent automation, AI decisioning and frontline teams.

Architecture & engineering

• Through the Functional/Technical Architects, define the AI/ML reference architecture (feature store, MLOps, GenAI platform, orchestration, integration with CRM, BSS/OSS, data lake and CDP) and ensure technical coherence with the BI & Data Engineering platform.
• Own vendor and technology selection for AI platforms, LLMs, automation tools and analytics products; manage build-vs-buy decisions and partner ecosystems (hyperscalers, system integrators, specialized boutiques).

Advanced analytics & delivery

• Through the Advanced Analytics Managers, deliver decisioning, propensity, churn, pricing, network and customer experience models that move commercial and operational KPIs.
• Industrialize delivery: enforce MLOps standards, model monitoring, A/B testing and value-tracking so use cases move beyond pilots and capture impact at scale.

Adoption, change & value capture

• Work hand-in-hand with business owners to drive adoption in the field — playbooks, training, frontline enablement, incentives — and to lock in value through P&L lines, not just dashboards.
• Define and report a transparent value-tracking model linking each use case to revenue, cost-to-serve, churn, NPS or capex avoidance.

Leadership & talent

• Lead, coach and develop a team of seven managers and their extended squads; build a high-performance engineering and analytics culture.
• Attract, develop and retain top AI, analytics and process-design talent in a competitive market; build a succession bench for the team's critical roles.

• University degree in Engineering, Computer Science, Mathematics, Statistics, Economics or related discipline; MBA or master's in Data Science / AI is a strong plus.
• 10+ years of progressive experience in analytics, data science, AI/ML, digital transformation or strategy consulting, including 5+ years leading multidisciplinary teams.
• Track record of delivering AI / advanced analytics use cases with measurable P&L impact in telecom, banking, retail, technology or consulting environments. Telco experience is highly valued.
• Hands-on familiarity with modern AI/ML stacks (Python, cloud ML platforms, MLOps), GenAI patterns (RAG, agentic workflows), and automation/process tooling (BPMN, RPA, low-code orchestration).
• Demonstrated ability to translate business problems into analytical products, prioritize a portfolio of use cases and capture value at scale — not just deliver pilots.
• Spanish and English business fluency required.

• University degree in Engineering, Computer Science, Mathematics, Statistics, Economics or related discipline; MBA or master's in Data Science / AI is a strong plus.
• 10+ years of progressive experience in analytics, data science, AI/ML, digital transformation or strategy consulting, including 5+ years leading multidisciplinary teams.
• Track record of delivering AI / advanced analytics use cases with measurable P&L impact in telecom, banking, retail, technology or consulting environments. Telco experience is highly valued.
• Hands-on familiarity with modern AI/ML stacks (Python, cloud ML platforms, MLOps), GenAI patterns (RAG, agentic workflows), and automation/process tooling (BPMN, RPA, low-code orchestration).
• Demonstrated ability to translate business problems into analytical products, prioritize a portfolio of use cases and capture value at scale — not just deliver pilots.
• Spanish and English business fluency required.

Strategy & roadmap

• Define and own the AI transformation strategy and multi-year roadmap for CWP, aligned with the corporate strategy, the LLA group agenda and the priorities of commercial, network, customer operations and finance.
• Build and continuously prioritize the portfolio of AI, GenAI and advanced analytics use cases — including business case, expected value, dependencies, risk and time-to-value — and present it to the Executive Committee.
• Establish AI governance, ethics, model-risk and responsible-AI standards in coordination with Legal, Risk, Cybersecurity and Data Privacy.

Process & workflow design

• Lead the Process/Workflow Designer Managers in re-engineering end-to-end customer and operational journeys (sales, care, fulfillment, assurance, billing/collections, retention) so they are AI-native and automation-ready.
• Define target operating models and human-in-the-loop designs that combine intelligent automation, AI decisioning and frontline teams.

Architecture & engineering

• Through the Functional/Technical Architects, define the AI/ML reference architecture (feature store, MLOps, GenAI platform, orchestration, integration with CRM, BSS/OSS, data lake and CDP) and ensure technical coherence with the BI & Data Engineering platform.
• Own vendor and technology selection for AI platforms, LLMs, automation tools and analytics products; manage build-vs-buy decisions and partner ecosystems (hyperscalers, system integrators, specialized boutiques).

Advanced analytics & delivery

• Through the Advanced Analytics Managers, deliver decisioning, propensity, churn, pricing, network and customer experience models that move commercial and operational KPIs.
• Industrialize delivery: enforce MLOps standards, model monitoring, A/B testing and value-tracking so use cases move beyond pilots and capture impact at scale.

Adoption, change & value capture

• Work hand-in-hand with business owners to drive adoption in the field — playbooks, training, frontline enablement, incentives — and to lock in value through P&L lines, not just dashboards.
• Define and report a transparent value-tracking model linking each use case to revenue, cost-to-serve, churn, NPS or capex avoidance.

Leadership & talent

• Lead, coach and develop a team of seven managers and their extended squads; build a high-performance engineering and analytics culture.
• Attract, develop and retain top AI, analytics and process-design talent in a competitive market; build a succession bench for the team's critical roles.