[Skip to main content](#main-content)

[OpenNash Jobs](https://jobs.opennash.com/)
[Hiring report](/reports/hiring/) · [All Ping An Insurance Group jobs](https://jobs.opennash.com/companies/ping-an-insurance/) · [Search jobs](/search/)

Ping An Insurance Group · 深圳市

# 模型风险管理岗

深圳市 

Listed on Ping An Insurance Group’s official careers site. Posted July 8, 2026. Check that it is still open and apply there.
[Apply on Ping An Insurance Group’s careers site →](https://talent.pingan.com/recruit/position.html?positionId=8E5B9D6172454EFFAF66D1DFD5DB53CF)

[OpenNash Jobs](https://jobs.opennash.com/) / [Ping An Insurance Group](https://jobs.opennash.com/companies/ping-an-insurance/) / 模型风险管理岗

## Job description

岗位职责
- 开展对公内评模型、预期信用损失模型的验证及持续监控，开展零售内评及评分模型的评审；
- 统筹全行信用风险模型风险管理工作，负责修订、完善模型风险管理相关的制度、机制，制定模型管理流程与标准；
- 组织全行信用风险模型评审，统筹开展投产前验证、持续监控，全流程模型风险管理；
- 负责推动资本计量高级方法的落地实施；
- 开展压力测试等其他风险计量管理工作。 任职资格
- 研究生及以上学历，数学、统计学、金融工程、数量经济学等相关专业为佳；
- 具有三年以上信用风险内评模型、评分卡模型、预期信用损失模型等开发或验证经验，覆盖对公、小微、零售领域；
- 数理统计知识扎实，熟悉最新算法，会使用SAS、PYTHON、R软件中至少一种；
- 具备良好的行文写作、沟通表达能力以及专业报告撰写能力。

## At a glance
- Posted by the employer: Jul 8, 2026
- First seen by OpenNash: Oct 20, 2026
- Last checked: Oct 20, 2026
- Listed for: 104 days
- Location: 深圳市[Apply on Ping An Insurance Group’s careers site →](https://talent.pingan.com/recruit/position.html?positionId=8E5B9D6172454EFFAF66D1DFD5DB53CF)

## More jobs at Ping An Insurance Group

### [1781D1-咨询顾问](https://jobs.opennash.com/companies/ping-an-insurance/jobs/95f48e90631a0bde553d/)

深圳市

### [1781F7-渠道专员](https://jobs.opennash.com/companies/ping-an-insurance/jobs/02d7c0f0340342f4423c/)

深圳市

### [2M售前支持岗——深圳](https://jobs.opennash.com/companies/ping-an-insurance/jobs/14becde09042cc988469/)

深圳市

### [:BK5283-项目管理岗](https://jobs.opennash.com/companies/ping-an-insurance/jobs/a4c4d5da5466f2de45b6/)

深圳市

### [AI Coding研发工程师](https://jobs.opennash.com/companies/ping-an-insurance/jobs/0565d10b2293019ec9b0/)

深圳市

OpenNash lists jobs from employers’ own careers sites and does not handle applications.
Dates come from the employer where stated; “first seen” and “last checked” are our own observations.

OpenNash Jobs · Official listings with dates and links to the employer. [Weekly hiring report](/reports/hiring/) · [Methodology](/methodology/)