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• Lead experimentation with advanced analytics and AI tools for productivity improvement, scenario modelling, and automated content generation (e.g., insights summaries, demand signals, trend reports)
• Integrate advanced analytics into existing products, evolving dashboards from static views into intelligent, self learning insight hubs
• Explore and assess the value of emerging technologies—LLMs, reinforcement learning, advanced optimization, and cloud native AI capabilities (Azure ML, Fabric, OpenAI).
• Champion the adoption of Responsible AI practices, ensuring transparency and ethical use of data science methods
• Develop, deploy, and maintain machine learning models, including forecasting, segmentation, optimization, and classification models used across regions and functions
• Work closely with other DnA team members and Technical Support/Operations on enhancement and maintenance requests as needed (particularly around model monitoring for things like drift or required retraining)
• Responsible for informing global data and analytics product owners about all requests/initiatives/ongoing work
• Responsible for assisting operations team with issues/changes to production analytics products for which they owned delivery
• Work with vendors as needed to support ongoing projects and operations:
• Maximize the value of our key partnerships
• Ensure that the partners deliver services that meet the business requirements and the agreed SLAs. Take corrective actions whenever not the case
• Align service requirements measures and scorecards with the partners

SKILLS

To be successful in this role you will have/be:

• Strong proficiency in data exploration and analysis, data modelling, SQL, Python, and visualization tools (Power BI preferred).
• Hands on experience building and evaluating machine learning models (regression, clustering, propensity scoring, timeseries forecasting, optimization).
• Familiarity with MLOps practices and cloud data science toolkits (Azure Machine Learning, Databricks MLflow, Microsoft Fabric AI services, CoPilot Studio, Azure AI Foundry)
• Strong proficiency of AI/ML concepts, including LLMs, prompt engineering, NLP, and automated insights generation
• Experience with large datasets, distributed computing, and data engineering fundamentals.
• Technical knowledge of data structures, architecture, visualization principles/tools, data analysis/exploration techniques
• Knowledge of analytics platforms, primarily SAP and Microsoft
• Highly collaborative with strong change agility
• Strong communication skills, including the ability to simplify technical concepts for senior leadership
• Understanding of IT governance and operations, IT controls (privacy, security)
• Experience/exposure to different markets dynamics/specificities/cultures
• Experience in crisis management, ability to manage the matrix
• Strong Ability to work with global teams