职位来源于实习僧。
岗位职责- 负责 FinFAST 平台全栈功能设计与开发落地，完成核心功能开发、API 接口开发，以及前端交互式数据看板搭建 搭建并维护数据链路，实时采集、处理、推送宏观经济指标、市场情绪数据及政策文件资料 对接大模型接口服务，为 AI 研究助手 FinBot 及各类智能产品功能提供技术开发支持 开发可视化图表组件，包含数据大屏、蛛网图、时间序列视图等，直观展示复杂经济数据
- 协同经济研究员、数据科学家，将业务研究需求转化为稳定可靠、可拓展的技术方案并落地实现
- 负责云端服务的部署运维、运行监控以及性能优化工作
- 参与代码审核、技术架构研讨，共同完善团队研发规范，提升整体工程研发质量
任职要求
- 本科及以上学历，须毕业于顶尖院校（或同等水平的海外顶尖院校） GPA 达到 3.5/4.0 及以上，或专业排名前 10% 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
- 精通 Python（后端开发 / 数据处理）及 JavaScript/TypeScript（前端开发）技术栈
- 熟练使用主流 Web 框架：前端掌握 React、Vue 或 Next.js，后端掌握 FastAPI、Django 或 Flask
- 熟悉关系型与非关系型数据库，具备 PostgreSQL、MongoDB 等数据库使用经验
- 精通 REST API 设计规范与接口集成方案
- 了解 AWS、GCP、Azure 等主流云平台，掌握 Docker、Kubernetes 等容器化技术
- 具备优秀的英文书面与口头沟通能力，中文流利者优先
加分项
- 具备大语言模型 API（OpenAI、Anthropic 等）生产环境集成落地经验
- 接触过彭博（Bloomberg）、万得（Wind）、CEIC 等金融数据平台，或有时序数据工程相关经验
- 掌握 ETL 数据管道设计与数据仓库架构搭建知识
- 具备经济学、金融或公共政策领域背景，或浓厚兴趣
- 有开源项目贡献经历
- 熟悉大模型相关技术：模型评估体系、提示词工程、向量数据库、向量嵌入开发、RAG 应用框架及内容安全过滤机制
Responsibilities
- Design and deliver end-to-end features for FinFAST: implement core functions, expose them via APIs, and build the interactive front-end dashboards
- Build and maintain data pipelines that ingest, process, and serve real-time macroeconomic indicators, sentiment signals, and policy documents
- Integrate large language model APIs to power FinBot, our AI research assistant, and other intelligent product features
- Develop interactive data visualisations — dashboards, spider charts, time-series views — that make complex economics intuitive
- Collaborate closely with economists and data scientists to translate research requirements into reliable, scalable software
- Own deployment, monitoring, and performance of your services in a cloud environment
- Participate in code review, architecture discussions, and contribute to a culture of engineering excellence
Requirements
- Strong proficiency in Python (backend/data) and JavaScript/TypeScript (frontend) Experience with a modern web framework — React, Vue, or Next.js on the front end; FastAPI, Django, or Flask on the back end Comfortable with relational and non-relational databases (PostgreSQL, MongoDB, or similar) Familiarity with REST API design and integration patterns Working knowledge of cloud platforms (AWS, GCP, or Azure) and containerisation (Docker, Kubernetes) Minimum GPA 3.5 / 4.0 or top 10% in cohort English proficiency: TOEFL 110+ or IELTS 7.5+ overall, with Reading and Writing sub-scores of 8.0 or above Bonus qualifications: Experience integrating LLM APIs (OpenAI, Anthropic, or similar) into production applications Exposure to financial data sources — Bloomberg, Wind, CEIC — or time-series data engineering Knowledge of ETL pipeline design and data warehouse architecture Background or interest in economics, finance, or public policy Contributions to open-source projects LLM ops: evaluation frameworks, prompt engineering, vector DBs (FAISS, Milvus, pgvector), embedding pipelines, RAG orchestration tools (LangChain/LlamaIndex) and safety filters
职位薪资
180-300/天
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