Data Architect & AI Engineering Lead, Cybersecurity - Assistant Vice President

Who we are looking for The Data Engineer / Data Scientist, Assistant Vice President, will provide technical and strategic leadership for enterprise cybersecurity data, analytics, and AI capabilities. This role will drive the architecture and delivery of scalable data platforms, advanced analytics, machine learning, graph analytics, NLP, and Generative AI solutions that convert complex security telemetry into actionable intelligence. The AVP will partner with cybersecurity, engineering, architecture, governance, and risk stakeholders to enhance threat detection, risk prioritization, operational efficiency, and executive decision-making while establishing scalable engineering and data science practices across the organization What you will be responsible for As a Data Engineer / Scientist, you will: ·       Design and deliver scalable data pipelines, Lakehouse architectures, data models, and analytics-ready datasets using Python, SQL, PySpark, Databricks, and cloud technologies. ·       Build reusable frameworks for data ingestion, transformation, aggregation, data quality, reconciliation, orchestration, lineage, and observability. ·       Develop statistical, machine-learning, and AI models to identify patterns, anomalies, relationships, threats, and risk signals across cybersecurity datasets. ·       Apply ML, graph analytics, NLP, and Generative AI to improve threat detection, vulnerability prioritization, incident enrichment, cyber-risk scoring, and security posture insights. ·       Develop AI solutions leveraging LLMs, embeddings, semantic/vector search, RAG, and intelligent workflows to summarize, classify, correlate, and enrich cybersecurity information. ·       Operationalize data science and AI solutions through feature pipelines, MLOps, CI/CD, automated testing, model monitoring, and production workflows. ·       Engineer and analyze high-volume structured, semi-structured, time-series, graph, and unstructured security data across cloud and enterprise platforms. ·       Build Power BI dashboards and self-service analytical products to communicate security trends, operational performance, risk insights, and model outcomes. ·       Establish strong engineering and responsible AI practices covering performance, scalability, resiliency, explainability, security, privacy, lineage, governance, and auditability. ·       Partner with cybersecurity, data and platform engineering, architecture, governance, risk, and product teams to translate complex security challenges into scalable data and AI solutions. ·       Evaluate emerging data engineering, ML, GenAI, graph, cloud, SIEM/SOAR, and cybersecurity technologies and drive their practical adoption. What we value These skills will help you succeed in this role: ·       Strong technical expertise across Data Engineering, Data Science, Machine Learning, and AI/GenAI.