QuantumGate is dedicated to developing and commercializing cutting-edge post-quantum cryptographic solutions. Our mission is to safeguard enterprise digital environments through innovative protocols and applications that address the evolving 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.. 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.

Responsibilities:

• Work closely with cryptographer and cyber security experts to translate 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 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).
• 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).

Requirements:

• 5+ 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
• 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.

Desired Skills:

• Cybersecurity domain familiarity, especially in one or more of: Cryptography (classical and post-quantum), PKI, certificate lifecycle, key management, vulnerability management.
• Experience with streaming or incremental ingestion (Kafka, CDC, timestamp-based deltas) and data observability.
• Background in applied research and/or publications in graph ML, security analytics, or related fields.
• Tableau, Power BI or Python libraries like Seaborn/Plotly.
• Ability to understand the "why" behind the data and its impact on the bottom line.
• Eagerness to stay ahead of the curve with the rapid evolution of data processing tools and frameworks.