Science, NetworkX, PyTorch Geometric or DGL; graph embeddings, pathfinding, similarity, clustering, link prediction, node classification, anomaly detection, and GNN development. • Programming and engineering: Advanced Python and SQL; APIs; test automation; data structures; distributed processing; Git; CI/CD; containers; infrastructure awareness; production debugging and performance optimization. • Data engineering: Spark … related discipline. • Demonstrated ownership of at least one production knowledge graph or graph analytics solution, preferably in cybersecurity. • Strong portfolio of hands-on Python and graph-query development, data pipeline engineering, testing, and production deployment. • Ability to translate complex security problems into data models, algorithms, measurable experiments, scalable services ...