技能档案

Data Visualization

此技能定义了各角色和级别的期望。

Data Engineering Data Visualization

角色数

包含此技能的角色

级别数

结构化成长路径

必要要求

其余 5 个可选

Data Engineering

Data Visualization

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。

各级别期望

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		Creates basic visualizations via matplotlib and seaborn: histograms, scatter plots, box plots, heatmaps. Visualizes feature distributions and correlations for EDA. Builds model metric charts: ROC curve, confusion matrix.

角色	必要性	描述
Data Scientist		Creates interactive visualizations via Plotly and Altair for data exploration. Builds informative dashboards in Streamlit for communicating results to stakeholders. Visualizes experiment and A/B test results with confidence intervals.

角色	必要性	描述
Data Scientist		Designs visualizations for explaining complex ML models: SHAP plots, partial dependence plots, attention maps. Creates custom visualizations for high-dimensional data via t-SNE/UMAP. Establishes visualization standards for the data science team.

角色	必要性	描述
Data Scientist		Defines data and ML results visualization standards for the organization. Establishes report templates for different stakeholders: technical, product, business. Coordinates creation of self-service analytics dashboards.

角色	必要性	描述
Data Scientist		Shapes data visualization strategy at organizational level. Defines tools and platforms for ML results visualization. Influences data-driven decision culture through visual communication quality.

Junior 1 要求

Data Scientist

Creates basic visualizations via matplotlib and seaborn: histograms, scatter plots, box plots, heatmaps. Visualizes feature distributions and correlations for EDA. Builds model metric charts: ROC curve, confusion matrix.

Middle 1 要求

Data Scientist

Creates interactive visualizations via Plotly and Altair for data exploration. Builds informative dashboards in Streamlit for communicating results to stakeholders. Visualizes experiment and A/B test results with confidence intervals.

Senior 1 要求

Data Scientist

Designs visualizations for explaining complex ML models: SHAP plots, partial dependence plots, attention maps. Creates custom visualizations for high-dimensional data via t-SNE/UMAP. Establishes visualization standards for the data science team.

Lead / Staff 1 要求

Data Scientist

Defines data and ML results visualization standards for the organization. Establishes report templates for different stakeholders: technical, product, business. Coordinates creation of self-service analytics dashboards.

Principal 1 要求

Data Scientist

Shapes data visualization strategy at organizational level. Defines tools and platforms for ML results visualization. Influences data-driven decision culture through visual communication quality.

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