Digital AI Engineer

Responsibilities:

• Analyze large datasets to extract valuable insights and identify trends.
• Develop systems for real-time data processing and analytics to provide immediate insights and responses.
• Develop and implement machine learning models to solve complex business problems.
• Continuously refine and optimize machine learning algorithms to improve accuracy and efficiency.
• Design and implement AI models to automate and enhance business processes.
• Develop predictive models to forecast trends, customer behaviors, and operational outcomes.
• Utilize NLP techniques to analyze and interpret unstructured data, such as customer feedback and documents.
• Work with cross-functional teams to understand data requirements and deliver actionable insights.
• Create and present detailed reports on findings, recommendations, and solutions.
• Promotes data culture, prepare knowledge sharing and education events relating to data usage

• Advanced degree in Data Science, Computer Science, Statistics, Mathematics or a related field.
• Knowledge in Azure AI and ML services such as Azure AI Foundry, Azure OpenAI, Azure AI Services, Azure Machine Learning, Azure Document Intelligence.
• Experience connecting Azure Data Environment with external AI LLM solutions
• Nice to have experience with AI services from AWS or GCP.
• Strong knowledge of statistical analysis and machine learning techniques
• Proficiency in programming languages such as Python or R, and experience with data visualization tools
• Min 2 years’ work experience with AI services
• Good knowledge of Data Management and Governance (MDM, Data Catalog, Taxonomy, Linage)
• Understanding of data supply & data demand and how to make data available

• Knowledge in Azure AI and ML services such as Azure AI Foundry, Azure OpenAI, Azure AI Services, Azure Machine Learning, Azure Document Intelligence.
• Experience connecting Azure Data Environment with external AI LLM solutions
• Familiarity with additional programming languages such as Python and R.
• Knowledge of Microsoft Azure cloud platform.
• Experience with AI and machine learning frameworks and libraries (e.g., TensorFlow, PyTorch).
• Understanding of AI model deployment and monitoring.
• Knowledge of security best practices and compliance standards in AI and cloud environments.