ML Engineer, Data Scientist

Summary

Join Strategy in Action, a pioneering Strategy-as-a-Service (SaaS) provider, as an exceptional ML Engineer / Data Scientist. You will design and implement a next-generation strategic intelligence system, connecting business strategy ontologies and knowledge graphs with large language models. This role involves ontology and knowledge graph development, LLM integration, and backend implementation. You will work at the intersection of knowledge engineering, artificial intelligence, and business strategy, shaping the future of strategic decision-making. The position offers a unique opportunity to contribute to a system that transforms how organizations develop and implement strategy, making world-class strategic thinking accessible to all. Competitive salary and a comprehensive benefits package are offered.

Requirements

• 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

Responsibilities

• 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

Preferred Qualifications

• 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

Benefits

Competitive salary based on experience, plus comprehensive benefits package (including equity options)