DATA ANALYST

1. Mission

  • Build a world-class data environment and provide services and automation tools tailored to users’ needs to help establishing a Data-Driven decision culture.
  • Measure UA campaign performances and identify optimization elements to support marketing team to ensure results.
  • Provide actionable insight by collecting and utilizing behavioral data to contribute to construction of the best user experience.

2. Role

  • Transform raw-data into actionable business tools.
  • Drive the improvement of measuring indicators and perform various A/B tests to help make decisions.
  • Help game development studios and other teams in publishing to make the right data-driven decisions based on improved indicators.
  • Challenges current processes within the organization and plays a key role in recommending improved KPIs.
  • Optimize performances by continuously tracking data and repeating development and verification of hypotheses. 

3. Required Competencies

[Duties]

  • Skills to diagnose/predict/prescribe data
  • Expertise in statistical theory, methods, and tools (SQL, Python, R, etc.)
  • Skills to effectively deliver complex insights and structured hypotheses to business stakeholders
  • Basic understanding of codes and skills to handle errors 
  • Good communication skills regardless of non-development/developmental job group

[Priority]

  • Practical business skills in data warehousing and business intelligence platforms
  • Experience in building clear, actionable dashboards by using data visualization technology and tools 
  • Experience in data analytics in startups with large user bases
  • Experience in expanding/transferring collected raw data in terms of business/product expectations
  • Deep understanding of the basic library of data science (Scikit-Learn, Pandas, NumPy, SciPy) and one or more deep learning frameworks (Keras, PyTorch, etc.)
  • Knowledge of various machine learning technologies (clustering, decision tree learning, artificial neural networks, etc.) and their practical advantages and disadvantages
  • Knowledge of advanced statistical skills and concepts (reverse, distribution attributes, statistical tests, appropriate usage, etc.) and skills to use applications
  • Competitive experience in Kagle

4. Technology Stack (some of the technologies we use)

  • Language : Python, Bash
  • Database : SQL (Impala, MySQL, PostgreSQL, SQLite) 
  • Ops: Git (Github/Gitlab)