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

[OpenNash Jobs](https://jobs.opennash.com/)
[Hiring report](/reports/hiring/) · [All Kuaishou Technology jobs](https://jobs.opennash.com/companies/kuaishou-technology/) · [Search jobs](/search/)

Kuaishou Technology · Beijing

# 策略开发实习生（内容生态方向）-【电商】

Beijing 

Listed on Kuaishou Technology’s official careers site. Listed as of October 19, 2026. Check that it is still open and apply there.
[Apply on Kuaishou Technology’s careers site →](https://zhaopin.kuaishou.cn/#/official/social/job-info/32176)

[OpenNash Jobs](https://jobs.opennash.com/) / [Kuaishou Technology](https://jobs.opennash.com/companies/kuaishou-technology/) / 策略开发实习生（内容生态方向）-【电商】

## Job description
- 基于内容生态业务场景，运用统计学/机器学习方法，设计并开发内容质量评估、风险识别、低质内容发现等方向的治理策略模型；
- 对平台内容数据进行深度挖掘，定位生态风险点与体验瓶颈，输出量化分析结论并驱动策略迭代；
- 参与内容分级分类策略的设计与开发，将生态治理规则转化为可执行的策略逻辑，保障治理策略的精准覆盖与低误判率；
- 建立策略效果评估框架，通过A/B实验、离线评测等方式持续衡量策略收益，推动策略调优与迭代闭环；
- 与产品、运营、内容安全等团队协同，参与从需求拆解到策略上线的全流程，确保策略落地的业务价值与技术质量。
- 数学、计算机科学、统计学、数据科学等相关专业 2027届硕士毕业生；
- 熟悉 Python / Java / R 中至少一种编程语言，具备扎实的模型基础和良好的算法能力；
- 逻辑思维清晰，语言表达与沟通能力良好，能够独立拆解复杂问题并推动解决；
- 每周可实习 5天，实习周期不低于 4个月。

## At a glance
- Posted by the employer: Not stated
- First seen by OpenNash: Oct 19, 2026
- Last checked: Oct 19, 2026
- Listed for: Under a day
- Location: Beijing[Apply on Kuaishou Technology’s careers site →](https://zhaopin.kuaishou.cn/#/official/social/job-info/32176)

## More jobs at Kuaishou Technology

### [(大模型专项）多模态大模型算法工程师](https://jobs.opennash.com/companies/kuaishou-technology/jobs/98edf462c05648daadcf/)

Beijing

### [AI Agent 开发实习生（电商在线推荐引擎）](https://jobs.opennash.com/companies/kuaishou-technology/jobs/5945a85b9a833fcbb5f8/)

Beijing

### [AI Agent 策略实习生](https://jobs.opennash.com/companies/kuaishou-technology/jobs/b814e14328b750da25f6/)

Beijing

### [AI Agent算法专家](https://jobs.opennash.com/companies/kuaishou-technology/jobs/0e36be4e740de43e02ad/)

Beijing

### [AI Agent算法专家（智能创作方向）](https://jobs.opennash.com/companies/kuaishou-technology/jobs/41a78c4c892cbbd1bc50/)

Beijing

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/)