At Trend Micro's Endpoint Module Team, the mission is to design and build advanced modules for threat protection. As a Data Scientist, you will collaborate with module developers, work with large-scale data, and apply analytical skills to deliver AI solutions for security engines. Responsibilities include designing, developing, and deploying scalable data infrastructures for monitoring engine feedback, providing data-driven insights to optimize module performance, and building machine learning and LLM-based models to detect and mitigate emerging threats.

Must Have

• Design, develop, and deploy scalable data infrastructures to monitor and analyze engine feedback data
• Collaborate closely with module developers, providing data-driven insights to optimize module performance
• Build machine learning models and LLM-based solutions to detect and mitigate emerging threats
• Proficient in Python and PySpark for large-scale data processing and analysis
• Familiarity with AWS analytics services
• Strong hands-on experience in designing, building, and deploying analytics solutions
• Skills of data story-telling and insight deliveries from complex datasets via analysis and visualization
• Broad knowledge of statistics, machine learning, and Large Language Models (LLM)

Good to Have

• Passion for data, with an innovative mindset and a keen interest in staying up-to-date with the latest data science techniques and trends
• Familiar with AI tools (Claude Code, Cursor)
• Experiences on MLOPS collaboration and MLOps tools and frameworks (e.g., MLflow, Kubeflow, Airflow)
• Knowledge of Windows system and threat behaviors

Overview

At Endpoint Module Team in Trend Micro, our mission is to design and build advanced modules that protect customers from ever-evolving threats.

As part of our team, you’ll collaborate closely with module developers, work with large-scale data, and leverage your analytical skills to deliver cutting-edge AI solutions for our security engines.

What You’ll Do

• Design, develop, and deploy scalable data infrastructures to monitor and analyze engine feedback data
• Collaborate closely with module developers, providing data-driven insights to optimize module performance
• Build machine learning models and LLM-based solutions to detect and mitigate emerging threats

Qualification/Requirement

• Minimum 3 years of professional experience as a Data Scientist, Data Engineer, or in a related analytical role
• Proficient in Python and PySpark for large-scale data processing and analysis.
• Familiarity with AWS analytics services
• Strong hands-on experience in designing, building, and deploying analytics solutions
• Skills of data story-telling and insight deliveries from complex datasets via analysis and visualization
• Broad knowledge of statistics, machine learning, and Large Language Models (LLM)
• Demonstrated ability to work independently to solve complex problems
• Skilled at translating complex technical concepts for stakeholders
• Good English communication skills

Nice to Have

• Passion for data, with an innovative mindset and a keen interest in staying up-to-date with the latest data science techniques and trends
• Familiar with AI tools (Claude Code、Cursor)
• Experiences on MLOPS collaboration and MLOps tools and frameworks (e.g., MLflow, Kubeflow, Airflow).
• Knowledge of Windows system and threat behaviors