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Open nowPosted 109 days ago

智能决策算法专家

weikezhijia/msxf4 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now智能决策算法专家weikezhijia/msxf · Beijing, Chinese Mainland

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  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 109 days ago

The posting

智能决策算法专家/高级专家 岗位职责 1. 贷后智能分案系统设计与开发 主导公司大模型项目在贷后管理场景的算法落地，设计并开发贷后智能分案系统。通过采集多源数据，利用大语言模型对非结构化文本数据进行深度语义分析，构建债务人画像向量（还款能力、还款意愿、风险等级、沟通偏好等维度），同时结合结构化数据特征，建立座席能力画像（历史业绩、擅长案件类型、沟通风格、合规表现等），实现贷后案件到人工座席的精准匹配。 2. 智能分案策略设计与迭代 设计AI辅助与人工作业的人机协作与分案机制，推动从传统规则分案向模型智能分案升级。构建基于多任务学习框架的分案策略预测模型，结合逾期阶段分层与用户画像驱动的动态决策引擎，输出最优分案建议并通过任务队列自动分配，提升作业效率、节省运营人力。 3. 反馈学习与模型迭代闭环 建立基于业务结果数据的闭环学习系统，持续采集分案效果数据（回收率、投诉率、案件处理时长等），驱动分案模型的自我优化和持续迭代。 4. 系统架构与工程落地 负责分案系统的算法架构设计，协同工程团队搭建场景化算法评估体系，保障模型从离线实验到线上生产的高效部署与稳定运行。 任职要求 基本条件： 硕士及以上学历，计算机、数学、统计学、人工智能等相关专业，博士优先；5年以上机器学习/推荐算法/NLP算法研发经验 精通Python，熟练使用PyTorch/TensorFlow等深度学习框架，熟悉LangChain、HuggingFace等大模型工具链 深入理解大模型微调技术（LoRA/QLoRA）、Prompt工程与Agent架构设计，熟悉Qwen、ChatGLM、DeepSeek等开源大模型原理与应用 核心能力要求： 有推荐算法、匹配排序、用户画像或智能调度类项目落地经验，具备从0到1搭建个性化匹配系统的能力 具备较强的业务抽象能力，能够将业务问题转化为建模任务 加分项（非必需）： 有金融风控、贷后管理、智能客服等领域经验者优先 有消金/互金行业从业背景者优先

智能决策算法专家/高级专家 岗位职责 1. 贷后智能分案系统设计与开发 主导公司大模型项目在贷后管理场景的算法落地，设计并开发贷后智能分案系统。通过采集多源数据，利用大语言模型对非结构化文本数据进行深度语义分析，构建债务人画像向量（还款能力、还款意愿、风险等级、沟通偏好等维度），同时结合结构化数据特征，建立座席能力画像（历史业绩、擅长案件类型、沟通风格、合规表现等），实现贷后案件到人工座席的精准匹配。 2. 智能分案策略设计与迭代 设计AI辅助与人工作业的人机协作与分案机制，推动从传统规则分案向模型智能分案升级。构建基于多任务学习框架的分案策略预测模型，结合逾期阶段分层与用户画像驱动的动态决策引擎，输出最优分案建议并通过任务队列自动分配，提升作业效率、节省运营人力。 3. 反馈学习与模型迭代闭环 建立基于业务结果数据的闭环学习系统，持续采集分案效果数据（回收率、投诉率、案件处理时长等），驱动分案模型的自我优化和持续迭代。 4. 系统架构与工程落地 负责分案系统的算法架构设计，协同工程团队搭建场景化算法评估体系，保障模型从离线实验到线上生产的高效部署与稳定运行。 任职要求 基本条件： 硕士及以上学历，计算机、数学、统计学、人工智能等相关专业，博士优先；5年以上机器学习/推荐算法/NLP算法研发经验 精通Python，熟练使用PyTorch/TensorFlow等深度学习框架，熟悉LangChain、HuggingFace等大模型工具链 深入理解大模型微调技术（LoRA/QLoRA）、Prompt工程与Agent架构设计，熟悉Qwen、ChatGLM、DeepSeek等开源大模型原理与应用 核心能力要求： 有推荐算法、匹配排序、用户画像或智能调度类项目落地经验，具备从0到1搭建个性化匹配系统的能力 具备较强的业务抽象能力，能够将业务问题转化为建模任务 加分项（非必需）： 有金融风控、贷后管理、智能客服等领域经验者优先 有消金/互金行业从业背景者优先

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