工作职责: 负责经济研究AI产品评测框架的设计与落地执行，全面测试模型在事实准确性、分析质量及领域专业度等核心维度的表现，保障产品输出可靠性。 联动资深经济学家，深度参与前沿研究工作，助力产出可影响投资策略的专业成果。 负责复杂数据集的处理与分析，将数据转化为可落地、有价值的决策洞察，为机构客户提供专业支撑。 搭建并持续迭代市场走势预测相关的经济模型，优化模型精度与实用性。 运用各类统计工具，实时追踪全球市场动态，深入分析新兴趋势，形成有参考意义的分析结论。 以创新视角参与产品全流程开发，推动分析方法、产品功能的迭代升级。 深度对接客户，精准挖掘并理解客户分析需求，提供超出预期的解决方案与服务。 任职要求: 学历要求：顶尖院校经济学硕士及以上（在读或已毕业）；或经济学本科，学业成绩优异，已获得保研资格、硕士/博士录取通知者亦可。 具备扎实的统计学、计量经济学及数据科学基础，能熟练运用相关理论开展分析工作。 至少熟练掌握一门数据分析编程语言（Python、R、SQL），能独立完成数据处理与分析任务。 具备出色的中英文分析、写作及口头表达能力，能清晰呈现分析成果、顺畅对接沟通。 工作严谨细致，对分析质量有极高要求，具备较强的责任心与执行力。 托福 110 分及以上，或雅思 7.5 分及以上（总分），且阅读、写作单项均不低于 8.0 分。 成绩要求：GPA达到3.5/4.0及以上，或专业排名前10%。 加分项: 有AI/大语言模型产品评测、基准测试或红队测试经验，尤其具备学术、量化研究场景相关经验者优先。 熟悉金融数据库的使用与洞察提取，包括但不限于Bloomberg、万得（Wind）、CEIC等。 了解数据仓库架构，具备ETL流程开发相关经验者优先。 拥有经济、金融及相关领域的实习或科研经历，有相关成果者优先。 Responsibilities: Design, build, and execute evaluation frameworks for AI products used in economic research — testing coverage, factual accuracy, analytical depth, and domain reliability Partner with senior economists on innovative research that shapes investment strategy Transform complex data sets into actionable intelligence for institutional clients Develop and refine economic models that predict market behavior Analyze emerging trends across global markets with sophisticated statistical tools Contribute directly to product development with fresh analytical approaches Engage with clients to understand and exceed their analytical needs Requirements: Education: Master's degree in Economics or a closely related field (enrolled or completed) or Economics undergraduate with confirmed graduate admission (Master's offer) and an outstanding academic record Solid grounding in statistics, econometrics, and data science fundamentals Proficiency in at least one analytical programming language — Python, R, or SQL Strong analytical writing and communication skills in both English and Chinese Meticulous attention to detail and commitment to analytical excellence TOEFL 110+ or IELTS 7.5+ overall, with Reading and Writing sub-scores of 8.0 or above Minimum GPA 3.5 / 4.0 or top 10% in cohort Bonus qualifications: Hands-on experience with AI/LLM product evaluation, benchmarking, or red-teaming — especially in academic or quantitative research contexts Experience navigating and extracting insights from financial databases (Bloomberg, WIND, CEIC, etc.) Expertise in data warehousing architecture and ETL pipeline development Prior internship or research experience in economics, finance, or a related field