Data Scientist

16 Years ago • 2 Years +

Job Summary

Job Description

This role requires a Data Scientist with 2+ years of experience in data analysis, machine learning, Python, and AWS/Azure. You will analyze customer data, design solutions, and develop algorithms for cybersecurity.
Must have:
  • Data Analysis
  • Machine Learning
  • Python Experience
  • AWS/Azure Skills
Good to have:
  • Hadoop/Spark
  • Devops (CI/CD)
  • Linux Programming
  • Threat Analysis
Perks:
  • Overseas Training
  • Impactful Mission

Job Details

As the number of cyberattacks and digital threats continue to grow, our world needs more passionate and innovative individuals who seek to be trailblazers in and shapers of the rapidly evolving cybersecurity landscape.

At Trend Micro, we offer tremendous opportunities that will challenge and equip you to become engineered to do good in whatever path you take. By choosing to be an agent of change, you will be part of an impactful mission that aims to make the world safe for exchanging digital information.

What you’ll do

Responsible for analyzing various kinds of customers data to find the security problems, doing POC and designing the end-to-end solutions based on machine learning or other data processing automation technique in AWS/Azure.

What you need

  • Bachelor’s degree in Computer Science or any related field
  • At least 2 years relevant experience
  • Excellent data analysis/presentation and storytelling
  • Machine Learning skills, being able to develop algorithms and to translate algorithms into code, completes programming, implements efficiencies, performs testing, and debugging.
  • Experience with Python
  • Good communication skill
  • Willing to be trained and be temporarily assigned overseas

What will help

  • Hadoop/Spark programming experience
  • Devops(CI/CD) experience
  • Linux application programming experience
  • Threat knowledge/threat analysis experience

#LI-DNI

Be Passionate.

Be Innovative.

Be a Trender.

Be #EngineeredToDoGood.

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Taipei City, Taiwan (On-Site)

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