Real resumes shared by CakeResume users.
1. Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
2. Master data analysis and other data science technologies to understand data.
3. Knowledge of a variety of statistical and machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and select AI/ML technologies to solve problems.
4. Strong problem solving skills with an emphasis on product development.
5. Cooperate with other departments to effectively use internal/external big data.
6. Experience working with and creating data architectures.
7. Excellent written and verbal communication skills for coordinating across teams.
8. Aggressively attend training courses, learn state of the art technologies and study top papers.
Education and Experience Qualifications:
1. Master, Department of Statistics/Applied Mathematic/Computer Science.
Requirements:
1. Experience querying databases and using statistical computer languages: R, Python, SQL, etc.
2. Knowledge and experience in statistical and data mining techniques: Regression, Random Forest, Boosting, Trees, text mining, etc.
3. Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, etc.
4. Experience analyzing data from 3rd party providers: Google Analytics, Facebook Insights, etc.
5. Can quickly master a new programming language.
6. At least 1-year experience of AI development or Data Analysis.
7. 薪資會依學經歷背景及相關工作經驗核薪
Other:
1. Passionate about researching AI, familiar with AI/ML technologies
2. Experience in Kaggle competition and fine-tuning Neural Network models
臺北市北投區立德路15號
