Social network you want to login/join with:We are seeking an exceptional ML Engineer / Data Scientist to design and implement our next-generation strategic intelligence system. You will play a crucial role in connecting business strategy ontologies and knowledge graphs with large language models like OpenAI, Anthropic and Gemini. This position offers a unique opportunity to work at the intersection of knowledge engineering, artificial intelligence, and business strategy. While prior experience is valued, we're primarily looking for intellectual horsepower, technical versatility, and genuine passion for knowledge representation systems.Key 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 structuresImplement ontology schemas in Neo4j or similar graph database systems. Create graph algorithms and queries to identify strategic patterns and insights from dataBuild 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 expertsLLM Integration (30%)Design the technical architecture connecting knowledge graphs with LLMs like OpenAI, Anthropic and GeminiDevelop context retrieval mechanisms that extract relevant subgraphs based on strategic queriesCreate prompt engineering templates that effectively incorporate knowledge graph structuresBuild response generation systems that combine graph analytics with LLM capabilitiesImplement feedback loops to improve the system's strategic reasoningBackend Implementation Collaboration (30%)Take ownership of technical components from concept to implementation. Present technical approaches, trade-offs and progress to stakeholdersCollaborate with other developers to implement robust and scalable production systemsDocument architecture decisions and implementation detailsWork directly with consultants and product managers, to understand strategic frameworks and use casesJob DescriptionAbout the RoleWe are seeking an exceptional ML Engineer / Data Scientist to design and implement our next-generation strategic intelligence system. You will play a crucial role in connecting business strategy ontologies and knowledge graphs with large language models like OpenAI, Anthropic and Gemini. This position offers a unique opportunity to work at the intersection of knowledge engineering, artificial intelligence, and business strategy. While prior experience is valued, we're primarily looking for intellectual horsepower, technical versatility, and genuine passion for knowledge representation systems.Key Responsibilities:Ontology Knowledge Graph Development (40%)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 structuresImplement ontology schemas in Neo4j or similar graph database systems. Create graph algorithms and queries to identify strategic patterns and insights from dataBuild 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 expertsLLM Integration (30%)Design the technical architecture connecting knowledge graphs with LLMs like OpenAI, Anthropic and GeminiDevelop context retrieval mechanisms that extract relevant subgraphs based on strategic queriesCreate prompt engineering templates that effectively incorporate knowledge graph structuresBuild response generation systems that combine graph analytics with LLM capabilitiesImplement feedback loops to improve the system's strategic reasoningBackend Implementation Collaboration (30%)Take ownership of technical components from concept to implementation. Present technical approaches, trade-offs and progress to stakeholdersCollaborate with other developers to implement robust and scalable production systemsDocument architecture decisions and implementation detailsWork directly with consultants and product managers, to understand strategic frameworks and use casesQualificationsRequired QualificationsBachelor's degree or Master’s Degree in Computer Science, Data Science, Information Science, or related field4-5 years of hands-on experience in Machine Learning, Data Science or Software DevelopmentExperience with graph database technologies (Neo4j preferred)Strong programming skills in PythonDemonstrated interest in knowledge representation, ontologies, or semantic technologiesFamiliarity with large language models and prompt engineeringAbility to translate conceptual frameworks into technical implementationsPreferred QualificationsExperience with ontology development tools and languages (OWL, RDF, Protégé)Background in NLP techniques for information extractionFamiliarity with LangChain, LangGraph, LlamaIndex, or similar LLM application frameworksExperience with business strategy concepts or frameworksContributions to knowledge graph or ontology projectsBackground in semantic web technologies or linked data principlesTechnical SkillsProgramming Languages: Proficiency with Python is mandatory. Knowledge of JavaScript is also beneficial.Graph Technologies: Neo4j, Cypher, GraphQLData Engineering: ETL pipelines, data integration patternsMachine Learning: NLP, embedding models, text classificationLLM Integration: Prompt engineering, context managementVisualization: Graph visualization tools and techniquesContainerization: Docker, KubernetesCloud Platforms: GCP familiarity is preferred (alternatively AWS or Azure).Personal AttributesExceptional analytical thinking and problem-solving abilitiesStrong communication skills to bridge technical and business conceptsSelf-motivated with the ability to work independently while collaborating effectivelyIntellectual curiosity and passion for knowledge representationComfort with ambiguity and ability to navigate evolving requirementsAttention to detail balanced with strategic thinkingCommitment to creating practical, business-focused solutionsAdditional InformationWhat You'll Do in Your First Six MonthsDesign and implement a core strategic ontology covering fundamental business strategy conceptsDevelop a proof-of-concept knowledge graph for a specific industry sectorCreate the initial integration connecting the knowledge graph with an LLMDemonstrate strategic use cases showcasing the system's analytical capabilitiesEstablish technical foundations for ongoing developmentWhy Join Strategy in ActionThis role offers the unique opportunity to shape the future of strategic decision-making at the intersection of structured knowledge and artificial intelligence. You'll be part of a pioneering team creating a system that fundamentally transforms how organizations develop and implement strategy. Working with both strategy experts and technical innovators, you'll help build technology that makes world-class strategic thinking accessible to organizations of all sizes. If you're passionate about knowledge representation and AI with an interest in business strategy, this role provides an exceptional growth opportunity with significant impact potential.Location(Flexible/Remote/Office Location)CompensationCompetitive salary based on experience, plus comprehensive benefits package (including equity options).Strategy in Action is an equal opportunity employer and values diversity in our organization.
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