Drive Digitalization: Collaborate cross-functionally with operations, quality control, and engineering teams to identify pain points and build practical, data-driven automation tools.
Integrate software engineering, quality assurance, devsecops, and mlops frameworks, guidelines and processes taking into account industry best practices, into software development activities.
Researching emerging AI/data science techniques and identifying relevant ones for EDB to explore and adopt (e.g. Agentic, LLM, Predictive, Fraud/Anomaly Detection, Text Analytics, Customer Segmentation)
Data Engineering and Integration: Build the data and knowledge pipelines required for AI use cases, with a focus on reliable ingestion, preparation, retrieval, and access-control-aware use of information.