
ML Engineer / Data Scientist
- Bari
- Tempo indeterminato
- Full time
- Design and develop comprehensive ontologies covering both company-specific strategic elements and industry-sector dynamics, following business strategy frameworks (SWOT, Porter's Five Forces, BCG Matrix, etc.)
- Create relationship taxonomies that capture complex strategic dependencies into formal knowledge structures
- Implement ontology schemas in Neo4j or similar graph database systems. Create graph algorithms and queries to identify strategic patterns and insights from data
- Build data pipelines to extract, transform, and load strategic data from various sources (e.g. LLMs own knowledge, structured data sources, unstructured documents)
- Balance theoretical rigor with practical applications in ontology design, to be validated with strategy experts
- Design the technical architecture connecting knowledge graphs with LLMs like OpenAI, Anthropic and Gemini
- Develop context retrieval mechanisms that extract relevant subgraphs based on strategic queries
- Create prompt engineering templates that effectively incorporate knowledge graph structures
- Build response generation systems that combine graph analytics with LLM capabilities
- Implement feedback loops to improve the system's strategic reasoning
- Take ownership of technical components from concept to implementation. Present technical approaches, trade-offs and progress to stakeholders
- Collaborate with other developers to implement robust and scalable production systems
- Document architecture decisions and implementation details
- Work directly with consultants and product managers, to understand strategic frameworks and use cases
- Bachelor's degree or Master's Degree in Computer Science, Data Science, Information Science, or related field
- 4-5 years of hands-on experience in Machine Learning, Data Science or Software Development
- Experience with graph database technologies (Neo4j preferred)
- Strong programming skills in Python
- Demonstrated interest in knowledge representation, ontologies, or semantic technologies
- Familiarity with large language models and prompt engineering
- Ability to translate conceptual frameworks into technical implementations
- Experience with ontology development tools and languages (OWL, RDF, Protégé)
- Background in NLP techniques for information extraction
- Familiarity with LangChain, LangGraph, LlamaIndex, or similar LLM application frameworks
- Experience with business strategy concepts or frameworks
- Contributions to knowledge graph or ontology projects
- Background in semantic web technologies or linked data principles
- Programming Languages: Proficiency with Python is mandatory. Knowledge of JavaScript is also beneficial.
- Graph Technologies: Neo4j, Cypher, GraphQL
- Data Engineering: ETL pipelines, data integration patterns
- Machine Learning: NLP, embedding models, text classification
- LLM Integration: Prompt engineering, context management
- Visualization: Graph visualization tools and techniques
- Containerization: Docker, Kubernetes
- Cloud Platforms: GCP familiarity is preferred (alternatively AWS or Azure).
- Exceptional analytical thinking and problem-solving abilities
- Strong communication skills to bridge technical and business concepts
- Self-motivated with the ability to work independently while collaborating effectively
- Intellectual curiosity and passion for knowledge representation
- Comfort with ambiguity and ability to navigate evolving requirements
- Attention to detail balanced with strategic thinking
- Commitment to creating practical, business-focused solutions
- Design and implement a core strategic ontology covering fundamental business strategy concepts
- Develop a proof-of-concept knowledge graph for a specific industry sector
- Create the initial integration connecting the knowledge graph with an LLM
- Demonstrate strategic use cases showcasing the system's analytical capabilities
- Establish technical foundations for ongoing development