Jobs at QuantumGate

QuantumGate is a startup within VentureOne, supported by the Advanced Technology Research Council (ATRC) and its research arm, the Technology Innovation Institute (TII). We specialize in developing and commercializing advanced post-quantum cryptographic solutions, with a mission to secure enterprise digital environments through cutting-edge protocols and applications that tackle the challenges of the post-quantum era.We are looking for a Senior Data Scientist to build and continuously improve the data models and the knowledge graph which will be the base of our Cryptography Discovery Tool. In this role, you will work closely with cryptographer and cyber security experts to articulate raw, complex data into strategic business action. You will own the technical approach for modeling, enriching, and operationalizing graph-based insights that support cryptographic asset visibility and security decision-making at enterprise scale.This is a hands-on role with end-to-end accountability: from schema/ontology design and entity resolution through data analytics, graph ML, evaluation methodology, and production integration.Key Responsibilities:Work closely with cryptographer and cyber security experts to translate vague business challenges into well-defined data science problems.Define and evolve the graph schema/ontology for security and cryptographic domains (e.g., certificates, keys, algorithms, protocols, applications, services, policies).Establish modeling standards (naming, constraints, provenance, versioning) and ensure explainability and auditability of graph-derived outputs.Architect pipelines to ingest and harmonize data from various sources.Lead entity resolution and record linkage, reconciling overlapping or inconsistent records produced by multiple collectors and data feeds (deduplication, identifier mapping, fuzzy matching, confidence-scored linking).Implement and monitor data-quality metrics: coverage, freshness, consistency, lineage, and confidence scoring.Develop graph-based analytics to surface security posture and cryptographic risk (centrality, community detection, blast-radius/dependency analysis, reachability queries)Apply graph ML techniques (embeddings, link prediction, anomaly detection) to infer missing relationships and prioritize remediation while maintaining interpretable results.Build evaluation frameworks and ground-truth strategies (offline benchmarks, human-in-the-loop validation, precision/recall, calibration of confidence scores).Explore and integrate Large Language Models (LLMs) and Generative AI frameworks to enhance product features and operational efficiency.\Design and develop an AI assistant that translates natural-language questions into validated, safe, and performant knowledge-graph queries (e.g., Cypher/Gremlin/SPARQL).Partner with engineering to productionize the assistant (authorization-aware query execution, rate limiting, logging/telemetry, and fail-safe fallbacks such as guided query builders or suggested refinements).Establish best practices for graph performance (indexing, query optimization, caching, incremental updates, timestamp-based deltas).Contribute to production readiness: testing, monitoring, incident triage, and post-deployment analytics.Mentor team members and influence cross-functional technical direction.Requirements:6+ years in data science, applied ML, or data/graph-focused roles (or equivalent experience), with demonstrated ownership of production-grade systems.Strong expertise in knowledge graphs and graph analytics, including graph data modeling and query languages (e.g., Cypher, Gremlin, SPARQL).Proven experience with entity resolution and working with real-world enterprise data at scale.Solid foundations in applied statistics/ML and the ability to design rigorous evaluation methodologies.Proficiency in Python and experience building data pipelines and collaborating with engineering on production deployments.Strong communication skills: ability to explain complex graph/ML approaches and tradeoffs to technical and non-technical stakeholders.Graph DB/query: Cypher/Gremlin/SPARQL.Data processing/orchestration: SQL, Hadoop stack, Spark/Databricks, Airflow.ML stack: scikit-learn, PyTorch; graph ML libraries (e.g., PyG, DGL).Experience working with large datasets.Join QuantumGate as we pioneer innovative solutions to secure the future of digital technology and protect tomorrow’s digital society.