LiveOps Team Senior Product Data Analyst

LiveOps Team Senior Product Data Analyst · Not Available, Hồ Chí Minh, Hồ Chí Minh.

• Bachelor’s degree in Business, Economics, Statistics, Math, Computer Science, or related majors.
• +3 years of experience in the data/analytics field.
• Strong product mindset, striving to improve user experience and product optimization; not stopping at data but providing product-driven solutions and consultation.
• Very good at logical thinking and able to learn new things quickly, attention to details.
• Strong analytics/statistics skills with experience working with a large amount of data (clean, visualize, extract insights, etc.).
• Strong experience using SQL/Python/R for data extraction and manipulation.
• Be confident to present the ideas and translating technical concepts and data into understandable reports/presentations.
• Be able to give clear and actionable recommendations based on data findings.
• Prefer experience on user segmentation modeling and product solutions based on models.
• Have a growth mindset, especially be comfortable with agile, strategic projects with ambiguous approaches.
• Nice to have: basic understanding of game industry and good command of English.
• Why You'll Love Working Here

• Shape personalization with 3B+ user data
• Grow in a mature, data-driven LiveOps team
• The Job
• About the team
• Inside our team:
• Strong data engineering foundation team with sustainable data pipelines.
• Highly mature Data team with a mindset of Data as a Product.
• Highly data-driven culture across multiple teams with a variety of data problems requiring diversified analytics methods. You will learn and grow deeply in Analytics while solving the problems.
• About the role
• As an Amanotes’ product Data Analyst, you have the chance to deal with data of 3+ billion users to generate accurate, actionable, and timely insights for the products team, in order to boost user understanding and product optimization
• What you will do
• Insights are key. We need deep-dive insights to improve user experience and product/process optimization, driving actions from top-down levels to bottom-up.
• Use analytical techniques such as EDA, statistical tests, time series analysis, funnel analysis, user journey analysis, clustering and other segmentation methods, etc. to extract patterns and user/product insights from behavioral user data.
• Conduct pre-AB test exploratory analysis to provide data-driven insights for product feature design.
• Conduct post-AB test deep-dive explanatory and exploratory analysis to validate key hypotheses, providing solid learning for next steps.
• Construct dashboards to monitor business performance.
• Proactively communicate with the business team (cross-functional teams) to understand their needs and to transform business questions into analytics and build data models to solve them.
• Collaborate closely with the Data Engineering team to understand the centralized data warehouse and pipeline, extracting data from multiple sources.
• Your Skills and Experience