- 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.
- 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
- 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
- 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)