领域
Machine Learning & AI
技能档案
此技能定义了各角色和级别的期望。
角色数
1
包含此技能的角色
级别数
5
结构化成长路径
必要要求
0
其余 5 个可选
Machine Learning & AI
Classical Machine Learning
2026/2/22
选择当前级别并对比期望。下方卡片显示晋升所需掌握的内容。
表格展示从初级到首席的技能深度变化。点击行查看详情。
| 角色 | 必要性 | 描述 |
|---|---|---|
| Data Scientist | Understands the fundamentals of Experiment Design. Applies basic practices in daily work. Follows recommendations from the team and documentation. |
| 角色 | 必要性 | 描述 |
|---|---|---|
| Data Scientist | Designs complex experiments: multi-variant tests, sequential testing, stratified randomization. Applies causal inference methods: difference-in-differences, instrumental variables. Calculates minimum detectable effect and plans experiment duration. |
| 角色 | 必要性 | 描述 |
|---|---|---|
| Data Scientist | Designs experimentation platforms for systematic A/B testing of ML models. Applies advanced methods: switchback experiments, cluster randomization, synthetic control. Establishes guardrail metrics and early stopping rules for safe experiments. |
| 角色 | 必要性 | 描述 |
|---|---|---|
| Data Scientist | Defines experimentation culture in the data science team. Establishes experiment design standards and review processes. Coordinates experimentation platform development and integration with ML pipelines. |
| 角色 | 必要性 | 描述 |
|---|---|---|
| Data Scientist | Shapes experimentation strategy at organizational level. Defines investments in experimentation infrastructure. Publishes methodological research on experiment design in ML contexts. |