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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Overview
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