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Tier-1 brand, metro location, mid-level Data Scientist role with broad ML and engineering requirements.
Strong data skills transferable, but cyber threat intelligence and security governance needs raise domain-specific sensitivity.
Mandatory 5+ years, strong SQL/Python, cloud and data engineering requirements, plus sensitive-data governance experience.
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Own the collection, processing, and analysis of large cybersecurity datasets to generate actionable insights using AI and machine learning.
Develop, maintain, and optimize data engineering pipelines and integrate cyber security data sources to support automated intelligence generation and AI adoption.
Produce real-time dashboards, reports, and secure API data feeds to support decision-making and cross-team collaboration within Cyber Threat Intelligence and Cyber Operations.
Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, Data Science, or related discipline (or equivalent).
At least 5 years of experience in data analytics, data science, or engineering roles, preferably in cybersecurity or similar domain.
Proficient in complex SQL queries and applied Data Science/Machine Learning using Python, TypeScript/Node.js, with solid cloud fundamentals (preferably AWS).
Certifications or formal training in analytics engineering/data modelling, cloud platforms (AWS Certified Data Engineer – Associate or equivalent), and Applied AI or Generative AI fundamentals.
Experienced in building and maintaining scalable data pipelines and automation for cybersecurity data ingestion and analysis, supporting CTI functions and AI strategies.
Capable of delivering complex data visualizations and real-time dashboards using tools like Power BI or Amazon QuickSight to inform security operations.
Skilled at managing sensitive data with governance practices (access control, encryption, audit logging) and integrating cyber threat intelligence data or security operations tools (e.g., TIP/SIEM).