腾讯Marketing Data Analyst (深圳)
任职要求
1.Bachelor's degree or above, with at least 5 years of experience in data analysis in the gaming/internet industry. 2.Familiar with market marketing data and analysis methods, with a certain level of understanding of overseas gaming, and hand-on experience in marketing. 3.Data-sensitive, logical, and proficient in …
工作职责
1.Responsible for overseas marketing data collection and analysis, establishing a data metrics system (monitoring, alerting, and interpretation) and visualizing, tooling, and systematizing it. 2.Provide preliminary data analysis and support based on the marketing pace of the gaming market, assist in marketing decision-making, and improve the efficiency of marketing resource utilization. 3.Monitor key marketing data, alert for data anomalies, promptly identify and locate issues, and mitigate related risks. 4.Assist in conducting comprehensive marketing performance reviews and analysis for projects, provide data-driven evaluations, and offer optimization recommendations. 岗位职责： 1. 负责海外营销数据统计与分析工作，搭建数据指标体系 (监控、预警与解读)，且能将其可视化、工具化、系统化 2. 根据游戏市场营销节奏，提供前置数据分析与支持，帮助营销决策，提高营销资源使用效率 3. 监控关键营销数据，对数据异常进行预警，及时发现并定位问题，规避相关风险 4. 协助项目进行各维度营销效果复盘与沉淀，提供数据化评估与后续优化建议 Work Location: China-Shenzhen
- Build data pipelines and integrate data from multiple sources; - Analyze data with scientific methodologies. Identify and quantify opportunities in product and packaging quality, manufacturing efficiency and consistency; - Design and develop AI agents to automate data analysis, opportunity identification, improvement action tacking and effectivenss evaluation; - Collaborate with cross-functional teams including Sourcing, Quality, Marketing, Business Management, Technology to identify automation opportunities, define use cases, and measure business impact - Continuously optimize existing automation solutions based on user feedback, business metrics and evolving business needs.
- Design and develop AI agents that automate workflows across product launch readiness, catalog quality management, supply chain visibility, and post-launch performance optimization - Build data pipelines and automation tools that integrate multiple data sources, enable real-time decision-making, and track key business metrics - Develop conversational AI assistant and detection systems that help business teams identify issues, prioritize actions, and improve operational efficiency at scale - Collaborate with cross-functional teams including Sourcing, Quality, Marketing, Business Management, Technology to identify automation opportunities, define use cases, and measure business impact - Continuously optimize existing automation solutions based on user feedback, operational metrics, and evolving business requirements A day in the life You'll start your day analyzing workflows and data to identify automation opportunities. You'll spend time building and testing AI agents using prompt engineering and coding tools, designing data pipelines, collaborating with business teams to refine requirements, and measuring the impact of your solutions on key metrics like launch readiness, operational efficiency, issue resolution speed, and time savings. You'll present findings to stakeholders and iterate on solutions based on feedback.
- Design and develop AI agents that automate workflows across product launch readiness, catalog quality management, supply chain visibility, and post-launch performance optimization - Build data pipelines and automation tools that integrate multiple data sources, enable real-time decision-making, and track key business metrics - Develop conversational AI assistant and detection systems that help business teams identify issues, prioritize actions, and improve operational efficiency at scale - Collaborate with cross-functional teams including Sourcing, Quality, Marketing, Business Management, Technology to identify automation opportunities, define use cases, and measure business impact - Continuously optimize existing automation solutions based on user feedback, operational metrics, and evolving business requirements A day in the life You'll start your day analyzing workflows and data to identify automation opportunities. You'll spend time building and testing AI agents using prompt engineering and coding tools, designing data pipelines, collaborating with business teams to refine requirements, and measuring the impact of your solutions on key metrics like launch readiness, operational efficiency, issue resolution speed, and time savings. You'll present findings to stakeholders and iterate on solutions based on feedback.
- Design and develop AI agents that automate workflows across product launch readiness, catalog quality management, supply chain visibility, and post-launch performance optimization - Build data pipelines and automation tools that integrate multiple data sources, enable real-time decision-making, and track key business metrics - Develop conversational AI assistant and detection systems that help business teams identify issues, prioritize actions, and improve operational efficiency at scale - Collaborate with cross-functional teams including Sourcing, Quality, Marketing, Business Management, Technology to identify automation opportunities, define use cases, and measure business impact - Continuously optimize existing automation solutions based on user feedback, operational metrics, and evolving business requirements A day in the life You'll start your day analyzing workflows and data to identify automation opportunities. You'll spend time building and testing AI agents using prompt engineering and coding tools, designing data pipelines, collaborating with business teams to refine requirements, and measuring the impact of your solutions on key metrics like launch readiness, operational efficiency, issue resolution speed, and time savings. You'll present findings to stakeholders and iterate on solutions based on feedback.