Machine Learning Scientist (Intern)

19 Hours ago • Upto 1 Years

About the job

SummaryBy Outscal

Must have:
  • Experience in data mining, algorithms, and machine learning
  • Experience in programming and statistical analysis
  • Ability to work independently and prioritize tasks
  • Build prediction or generation models
  • Extract valuable info from large datasets
Good to have:
  • Meta-cognition
  • Applying past knowledge to new situations
  • Clear and precise communication
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About Appier 

Appier is a software-as-a-service (SaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.

About the role

The Machine Learning Scientist internship involves researching, developing, and applying Machine Learning  techniques.

We are seeking potential candidates who can commit to 2-3 days a week and participate in the internship for a minimum of 6 months, starting immediately. Please ensure that you have checked your availability before applying.

Responsibilities

  • Use machine learning and analytical techniques to build prediction or generation models
  • Experience in analyzing and extracting valuable information from large amounts of business data
  • Co-operate with software engineering teams to drive real-time model implementations and new feature creations
  • Research and evaluate pioneering machine learning and statistical model


About you

[Minimum qualifications]

  • Experience in data mining, algorithms, statistical analysis, LLM and/or machine learning
  • Experience in programming, ability to work independently to revise system and model
  • Self-motivation and an ability to priorities multiple competing challenges in a fast-growth environment

[Preferred qualifications]

  • Thinking about thinking; meta-cognition
  • Applying past knowledge to new situations
  • Thinking and communicating with clarity and precision
  • Remain open to continuous learning
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