Senior Machine Learning Scientist, Advertising Incrementality

2 days ago

Taipei, Taiwan Appier Full time $100,000 - $120,000 per year

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: Visit  for more information.

The Impact You'll Make at Appier

Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team, which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery.

In this role, you'll measure ads incrementality on different type of traffic, creative, users, and also improve campaign efficiency on combination having good incrementality by machine learning model and AI automation.

 

What You'll Work On

  • Leverage scientific methods to improve ads measurement.
  • Drive online experiments to continuously improve ads effectiveness.
  • Own the project independently.
  • Partner with product stakeholder, backend and frontend to provide measurement solution for our customers.
 

What We're Looking For

  • Master's or PhD's degree in Computer Science, Machine Learning, Statistics, Econometrics, or related field.
  • 3+ years of industry experience on causal inference, incrementality, marketing mix modeling or other measurement solutions on digital Ads related fields, and understand the assumption and difference across methods.
  • Proficiency in Python and SQL experience with modern ML frameworks (PyTorch, TensorFlow, etc.).
  • Strong ownership and collaboration skills.

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