About Gen:
Gen (NASDAQ: GEN) is a global company dedicated to powering Digital Freedom through its trusted consumer brands, including Norton, Avast, LifeLock, MoneyLion, Avira, AVG, CCleaner, GOBankingRates, ReputationDefender, and Trellis Technologies. Gen brings award-winning products and services in cybersecurity, online privacy, identity protection, financial wellness, and insurance to nearly 500 million users in more than 150 countries.
Working at Gen is more than just a job. It’s where passion meets purpose, driving our mission to power Digital Freedom. Our culture fosters collaboration, innovation, and a giving mindset—enabling our team to deliver exceptional employee experiences and a positive impact to the world around us.
About the Role:
The Classification & Labelling team is the foundation of Gen’s automated detection capabilities—every AI model is only as good as the ground-truth data it learns from.
As a Junior Threat Analyst / Labeller, you will label and classify threat samples across the SafeSMS, EmailGuardian, AI Assistant and other detection pipelines, triage false positive and false negative submissions from our FP solving system, and support senior analysts with classification decisions that directly determine detection accuracy for millions of Gen customers.
Don’t be put off if you’re new to security—we will teach you what you need to know.
What You’ll Do:
Label incoming threat samples across SafeSMS, EmailGuardian, AI Assistant, and other detection pipelines (scam messages, phishing URLs, deepfakes, AI-generated threats).
Triage FP/FN submissions from FP solving system: investigate misclassifications and escalate edge cases to senior analysts.
Manage and classify email and SMS threat clusters consistently and at volume.
Support senior analysts with research and classification decisions on novel or ambiguous samples.
Participate in data analysis projects that feed into detection pipeline improvements.
Document classification rationale clearly in Jira and internal labelling systems.
Take part in regular calibration sessions to keep labelling standards consistent across the team.
What You’ll Need:
Minimal understanding of common threat types: phishing, scams, social engineering, malicious URLs, and others
Ability to assess threat indicators: message content, URLs, sender metadata, file metadata is a plus
Familiarity with scripting or programming languages (Python, PowerShell or others) is a plus
Strong attention to detail—accuracy and consistency at volume is the core of this role
Ability to work independently and in a team-oriented environment
Clear written communication for documenting classification decisions and escalation notes
English level B2 or higher—analysis and documentation is in English
What We Welcome, or Will Teach You:
Scam detection techniques across SMS, email, and AI-generated content
Malware identification methods and internal classification guidelines
FP solving system triage workflows and incident response scenarios
Python or scripting basics for handling samples at scale
