GCS, Data Scientist, AVP

Quick Facts

• Role: Data Scientist (cybersecurity data science and analytics)
• Focus: statistical modeling, machine learning, graph analytics, NLP, and GenAI on large-scale security datasets

Description

Develop predictive, explainable, and actionable intelligence from cybersecurity telemetry and operational data to improve risk prioritization, threat detection, vulnerability prioritization, incident enrichment, cyber risk scoring, and security posture measurement.

Responsibilities

• Develop statistical, machine-learning, and AI-driven models to identify patterns, anomalies, relationships, and risk signals across enterprise cybersecurity datasets.
• Analyze structured, semi-structured, graph, time-series, and text-based security data using Python, SQL, PySpark, and Databricks.
• Design and deliver analytics for threat detection, vulnerability prioritization, incident enrichment, cyber risk scoring, and security posture measurement.
• Apply graph analytics and network science to relationships among identities, assets, vulnerabilities, applications, alerts, events, and threat indicators.
• Use NLP and GenAI to summarize, classify, enrich, and operationalize cybersecurity data (alerts, tickets, logs, findings, playbooks, and investigation notes).
• Build reusable analytical datasets, features, notebooks, models, dashboards, and model-monitoring outputs that scale across enterprise security use cases.
• Partner with cybersecurity analysts, data engineers, platform engineers, architects, risk teams, and product owners to translate business and security needs into analytical solutions.
• Create Power BI reports and self-service dashboards for technical and non-technical audiences.
• Support responsible model development practices: validation, performance monitoring, explainability, privacy, security, lineage, and documentation in a regulated environment.
• Continuously evaluate emerging analytics/ML/graph/NLP/GenAI/SIEM/SOAR/cloud data capabilities for practical cybersecurity outcomes.

Requirements

• 5-8 years of total professional experience in data science, analytics, machine learning, data engineering, or related technical roles.
• 2-4 years of experience applying data science/analytics/ML techniques to cybersecurity, risk, fraud, infrastructure, identity, or similarly complex enterprise datasets.
• Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Cybersecurity, Information Systems, or equivalent practical experience.
• Strong hands-on experience with Python and SQL for analytical modeling, exploratory analysis, statistical evaluation, and data manipulation.
• Experience using PySpark and Databricks to process, analyze, and model large-scale datasets.
• Experience creating clear, actionable dashboards and visualizations using Power BI or similar BI tools.
• Working knowledge of AWS data and analytics services or other cloud-based analytical environments.
• Familiarity with SIEM/SOAR platforms and security workflows (alert enrichment, detection analytics, triage, response, reporting).
• Experience applying advanced analytical methods such as graph analytics, NLP, GenAI, anomaly detection, classification, clustering, forecasting, or recommendation.
• Strong written and verbal communication skills to document assumptions, model limitations, and recommended actions.
• Individual contributor role with strong cross-functional collaboration.
• Ability to use sound judgment with sensitive cybersecurity, risk, operational, and regulated data.
• Comfort balancing exploratory data science with production-minded delivery and stakeholder communication.

Benefits

• Retirement savings plan (401K) with company match.
• Insurance coverage: basic life, medical, dental, vision, long-term disability, and optional additional coverages.
• Paid time off: vacation, sick leave, short term disability, and family care responsibilities.
• Employee Assistance Program.
• Incentive compensation with eligibility for annual performance-based awards (excluding certain sales roles).
• Eligibility for certain tax advantaged savings plans.