Data Scientist, Analytics

Taipei, Taiwan

Applications have closed

Appier

Comprehensive AI-Powered Solutions: Smoother Operaions. Elevated Customer Experience. Better Performance.

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Appier is an AI SaaS company on a mission to make AI easy, by making software intelligent. Founded in 2012, Appier has 17 offices across APAC, U.S. and Europe and is listed on the Tokyo Stock Exchange. Visit www.appier.com for more information.

About the role

We are looking for Data Scientists in Taiwan that will be part of our data science team. You will work closely with Machine Learning Scientists, Engineers, and other product related roles to perform data analytics for achieving Appier’s product and business goals.

 

Task of the role

  • Drive initiatives and experimentations in CrossX product (e.g., enhance the efficiency to deliver ads to end users in real-time-bidding scenarios). 
  • Evaluate and define product and business metric framework.
  • Build key data sets/pipelines to empower operational and exploratory analysis.
  • Conduct data analysis reports to illustrate the results and insight (dashboards, reports)

 

About you

[Essential]

  • 2+ years of industry experience in the data analytics area.
  • Can write efficient Python scripts for data analysis and job automation.
  • Statistics knowledge and skills, using SQL to do basic data extraction and aggregation. 
  • Sufficient know-how of machine learning and basic experience of using machine learning tools.
  • Fluent in Pandas or PySpark.
  • Good analytical skills to extract meaningful insights from the data.
  • Ability to communicate data analysis insight to audiences with different backgrounds.
  • Proficient oral and written communication skills in English.

 

[Nice to have]

  • Working experiences in digital advertising industries.

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Data analysis Data Analytics Machine Learning Pandas Pipelines PySpark Python SQL Statistics

Region: Asia/Pacific
Country: Taiwan
Job stats:  12  1  0

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