这是一个创建于 2713 天前的主题，其中的信息可能已经有所发展或是发生改变。
中国领先的大数据信用评估平台闪银 Wecash，通过先进的风控技术撮合金融机构、服务提供方和个人消费者，帮助金融机构降低风险，帮助消费者更轻松便捷享受到更好的服务。解决了传统金融风控“周期长”“门槛高”“资料繁琐”“脸难看”“事难办”等弊端，闪银在数秒内完成信用决策，并在 15 分钟内撮合用户与金融机构，让这个周期缩短至分钟，用户体验得到了极大的提升。
闪银成立于 2014 年 4 月，互联网金融行业发展之初，成立以来实现了每年以 10 倍的高速增长。闪银的业务并未选择互金创业风口做 P2P，而是卡住了行业发展的关键路径，从互联网数据信用评估切入业务。闪银依靠创新的业务模式和自主研发的风控技术，累计为超过 8000 万用户匹配了来自 50 家金融机构的超过 150 亿元的金融服务，信用评估体系完成累计超过 40 亿次的数据调用。闪银研发的大数据风控系统先后获得毕马威、德勤、世界银行等知名机构的认可，闪银被选入了埃森哲亚太区金融技术创新实验室，德勤评选的“明日之星”并获得了毕马威颁发的 Fintech 全球金融科技创新 50 强等荣誉称号。
公司地点：北京市朝阳区农展馆南路 13 号瑞辰国际中心 [总部]
职位 BASE：美国旧金山
乘车路线：10 号线团结湖 B 口出，东行 500 米
投递邮箱： [email protected]
欢迎有意向的伙伴积极投递简历，人力资源部将在第一时间和你取得联系，请耐心等待我们的沟通电话
如有疑问欢迎加微信沟通 18211082613 小石头
Responsibilities will include:
- Lead and manage the data science team and work closely with product and engineering team to integrate the credit risk models into the product flows
- Research and develop the algorithms and models for efficiencies and cost reductions on different stages including user acquisition, loan application, loan behavior and collection.
- End to end hands-on ownership of machine learning systems deployable across various projects including data pipelines, model training, and model monitoring.
- Provide the analytical/quantitative input to develop, document, implement and monitor the build of complex consumer credit risk loss forecasting, reserve, and capital models.
- Execution with precision and working to manage internal and external dependencies to deliver quality model on time and on budget.
- Creates and sustains an environment of ingenuity and creativity and challenges the status quo to encourage innovation
Skills Required:
- Advanced degree (M.S. or PhD) in a quantitative discipline, e.g., economics, statistics, mathematics, computer science, engineering or finance
- At least 2 year's experience working in a field using machine learning and other predictive modelling techniques, engineering, statistics, mathematics etc.
- Senior stakeholder engagement and effective line management experience
- Strong attention to detail
- Tech savvy, Problem solver
- High degree of self-confidence, humility and energy for using data and algorithm to drive underwriting decisions
- Good communication skills (verbal, writing, presentation) in both Chinese and English, with Portuguese preferred
闪银成立于 2014 年 4 月，互联网金融行业发展之初，成立以来实现了每年以 10 倍的高速增长。闪银的业务并未选择互金创业风口做 P2P，而是卡住了行业发展的关键路径，从互联网数据信用评估切入业务。闪银依靠创新的业务模式和自主研发的风控技术，累计为超过 8000 万用户匹配了来自 50 家金融机构的超过 150 亿元的金融服务，信用评估体系完成累计超过 40 亿次的数据调用。闪银研发的大数据风控系统先后获得毕马威、德勤、世界银行等知名机构的认可，闪银被选入了埃森哲亚太区金融技术创新实验室，德勤评选的“明日之星”并获得了毕马威颁发的 Fintech 全球金融科技创新 50 强等荣誉称号。
公司地点：北京市朝阳区农展馆南路 13 号瑞辰国际中心 [总部]
职位 BASE：美国旧金山
乘车路线：10 号线团结湖 B 口出，东行 500 米
投递邮箱： [email protected]
欢迎有意向的伙伴积极投递简历，人力资源部将在第一时间和你取得联系，请耐心等待我们的沟通电话
如有疑问欢迎加微信沟通 18211082613 小石头
Responsibilities will include:
- Lead and manage the data science team and work closely with product and engineering team to integrate the credit risk models into the product flows
- Research and develop the algorithms and models for efficiencies and cost reductions on different stages including user acquisition, loan application, loan behavior and collection.
- End to end hands-on ownership of machine learning systems deployable across various projects including data pipelines, model training, and model monitoring.
- Provide the analytical/quantitative input to develop, document, implement and monitor the build of complex consumer credit risk loss forecasting, reserve, and capital models.
- Execution with precision and working to manage internal and external dependencies to deliver quality model on time and on budget.
- Creates and sustains an environment of ingenuity and creativity and challenges the status quo to encourage innovation
Skills Required:
- Advanced degree (M.S. or PhD) in a quantitative discipline, e.g., economics, statistics, mathematics, computer science, engineering or finance
- At least 2 year's experience working in a field using machine learning and other predictive modelling techniques, engineering, statistics, mathematics etc.
- Senior stakeholder engagement and effective line management experience
- Strong attention to detail
- Tech savvy, Problem solver
- High degree of self-confidence, humility and energy for using data and algorithm to drive underwriting decisions
- Good communication skills (verbal, writing, presentation) in both Chinese and English, with Portuguese preferred
目前尚无回复
Select Language