Job Description

Join Trend ‧ Join New Generation

趨勢科技 - 全球雲端資安領航者 / 全亞洲最大軟體公司 / 企業版圖橫跨五大洲 / 趨勢全球研發基地在台灣
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AI is currently at the forefront of technological advancement, marking a transformative shift across industries. As a global cybersecurity leader, Trend Micro is committed to staying at the cutting edge of this evolution. You will work with large-scale data, deliver AI solutions, and collaborate with threat experts to enhance cybersecurity for millions of users.

We are building an AI-native engineering organization That means AI is not an optional accelerator — it is a core part of how we design, build, test, and ship. We are looking for data scientists who have already established their own AI-driven development workflows and are ready to bring that mindset to petabyte-scale, security-critical problems.

What You'll Do

• Drive the full data science lifecycle with AI at every stage — from problem framing and feature engineering, through model development, evaluation, deployment, and monitoring — using tools like Claude Code, GitHub Copilot, or Cursor as a first-class part of your workflow.
• Design, develop, and deploy scalable data processing pipelines to support AI-driven threat detection and cybersecurity solutions.
• Work with petabyte-scale datasets from diverse sources, applying advanced statistical analysis, data mining, and machine learning techniques.
• Build and optimize machine learning models to detect and mitigate emerging threats in real time.
• Collaborate closely with threat researchers, security analysts, and product teams to translate complex security patterns into deployable AI solutions.

How You'll Adopt AI

• Established a repeatable AI-native development workflow for data science tasks — from EDA and feature engineering to model iteration and documentation.
• Practices context engineering: actively managing what is given to AI tools to produce high-quality, project-appropriate outputs such as analysis code, model architectures, and experiment writeups.
• Familiarity with AI-native tools (e.g., Claude Code, GitHub Copilot, Cursor) and how to configure them for a data science codebase (e.g., CLAUDE.md, Cursor Rules).
• Validates AI-generated code and analysis — reviewing logic, statistical soundness, edge cases, and alignment with security domain requirements.
• Experience building or using Agent Skills or MCP servers to extend AI capabilities within a data or research workflow.

Qualification / Requirement

• Minimum 4 years of professional experience as a Data Scientist or in a related analytical role.
• Proficient in Python and PySpark for large-scale data processing and analysis.
• Familiarity with cloud-based big data platforms (e.g., AWS EMR, Google Cloud Dataproc, Azure Databricks).
• Strong hands-on experience in designing, building, and deploying machine learning models and pipelines.
• Solid computer science fundamentals, including a deep understanding of algorithms, data structures, data modeling, and system programming.
• Broad knowledge of statistics, data mining, machine learning, and artificial intelligence algorithms.
• Demonstrated ability to work independently to solve complex problems.
• Excellent communication skills and the ability to translate complex technical concepts into actionable business insights.

Nice to Have

• Experience driving measurable improvements in team or research productivity through AI workflow adoption.
• Experience or understanding of email threat detection, email security, or related cybersecurity domains.
• Previous publications or presentations in top-tier ML conferences or journals (NeurIPS, ICML, KDD, AAAI, CVPR).
• Experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, Airflow).
• Proficiency in SQL and experience with relational and NoSQL databases.
• Experience building or maintaining internal AI tooling (agent pipelines, prompt template libraries, MCP servers).

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連結智慧 守護世界 --- Connected Intelligence for Securing a Connected World