Job Description :

Key Responsibilities :

1. Drive Revenue Growth & Commercial Excellence :

- Design and deploy AI-driven capabilities such as : Lead prioritization models, Opportunity scoring and pipeline intelligence, Next-best-action recommendations

- Improve sales productivity through workflow automation and intelligent insights

- Build integrated commercial analytics across CRM, marketing, and customer datasets

- Enable visibility into pipeline health, conversion metrics, and forecast performance

2. Strengthen Forecasting & Business Analytics :

- Develop advanced forecasting models using historical, market, and behavioural data

- Standardize key commercial KPIs across regions and business units

- Build scalable self-service analytics layers for business teams

- Establish strong data governance frameworks ensuring accuracy, lineage, and transparency

3. Optimize Supply Chain & Operations :

- Implement AI-led demand planning and predictive analytics models

- Improve inventory management through optimized policies and planning parameters

- Develop simulation models for supply-demand and capacity planning

- Partner with manufacturing and supply chain teams to embed predictive insights into decision-making

4. Reduce Supply Chain & Logistics Costs :

- Build optimization models for : Transportation and routing; Network design and logistics planning

- Identify key cost drivers and efficiency opportunities in supply chain operations

- Implement early-warning systems for disruptions and delays

- Recommend data-driven improvements in planning cycles and network efficiency

5. Architect Enterprise AI Ecosystem :

- Define and govern enterprise-wide AI architecture across: Commercial systems (CRM, marketing tools); Operations systems (ERP, manufacturing platforms)

- Establish robust integration patterns across ERP, CRM, and collaboration platforms

- Design scalable, secure, and governed data pipelines

- Standardize data models, taxonomies, and semantic layers across functions

6. Lead Adoption & Change Management :

- Drive enterprise-wide AI adoption through : Role-based training programs; Communication strategies and playbooks

- Build and manage a network of business champions

- Track adoption metrics, value realization, and performance impact

- Partner with business leaders to drive process transformation and behavioural change

Key Stakeholders :

- Growth & Innovation Teams

- IT & Digital Functions

- Commercial Leadership

- Manufacturing & Supply Chain Teams

- OpCo General Managers

- Corporate Functions (Finance, HR)

Scope :

- Selection of AI models, solution architecture, and analytics approaches

- Technology stack decisions within Microsoft and Azure ecosystem

- MLOps strategy, deployment, and release cycles

- Prioritization of technical scalability and system improvements

- Business case development and AI investment decisions

- Data governance, privacy, and compliance alignment

- KPI definition and process design with commercial and operations leaders

Qualifications & Experience :

Education :

- Bachelors degree in computer science, Data Science, Engineering, or related field

- Masters degree preferred

Experience :

- 10- 15+ years in AI/analytics, solution architecture, or enterprise data platforms

- Proven experience in deploying AI solutions at scale in enterprise environments

- Strong exposure to Microsoft ecosystem (Azure AI, Power Platform, Dynamics 365)

- Experience working with ERP systems (SAP preferred)

- Background in manufacturing, supply chain, or operations analytics is highly desirable

Technical & Functional Expertise :

- AI/ML model development and deployment

- Data modelling, integration frameworks, and automation

- Commercial analytics and sales pipeline optimization

- Supply chain analytics and optimization techniques

- Cloud architecture (Azure) and MLOps practices