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:

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 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

LLM Integration (30%)

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

Backend Implementation & Collaboration (30%)

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

Qualifications

Required Qualifications

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

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

Technical Skills

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).

Personal Attributes

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

Additional Information

What You'll Do in Your First Six Months

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

Why Join Strategy in Action

This 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]

Compensation

Competitive 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.