# Career Path For

Data Analyst

in 2022

#### Looking for Data Analyst career path for? This is an ultimate list of career path for for Data Analyst.

# Career Path career path for Data Analyst

## Junior Data Analyst

### Skills needed for Junior Data Analyst

- Knows the theory, but has not applied it T-statistic
- Knows the theory, but has not applied it Histogram
- Knows the theory, but has not applied it Libraries
- Knows the theory, but has not applied it Bar plot
- Knows the theory, but has not applied it Models creation
- Knows the theory, but has not applied it Python
- Knows the theory, but has not applied it Boxplot
- Knows the theory, but has not applied it Writing a presentation
- Knows the theory, but has not applied it Heatmaps
- Knows the theory, but has not applied it Cross-validation
- Knows the theory, but has not applied it Go
- Knows the theory, but has not applied it Markdown
- Knows the theory, but has not applied it Hierarchical
- Knows the theory, but has not applied it Data normalization methods
- Knows the theory, but has not applied it Algorithms
- Knows the theory, but has not applied it K-means
- Knows the theory, but has not applied it Dbscan
- Knows the theory, but has not applied it Metrics
- Knows the theory, but has not applied it ANOVA test
- Knows the theory, but has not applied it Scatter plots
- Knows the theory, but has not applied it Bottom-up/Top-down approaches
- Knows the theory, but has not applied it P-value and acceptable values
- Knows the theory, but has not applied it Calculation of mean/median/mode/variance/coefficient. variations
- Knows the theory, but has not applied it Coef. Pearson, Spearman correlations
- Knows the theory, but has not applied it Countplot
- Knows the theory, but has not applied it Line plots

## Middle Data Analyst

### Skills needed for Middle Data Analyst

- Knows the theory, but has not applied it Hierarchical
- Knows the theory, but has not applied it K-means
- Knows the theory, but has not applied it Boxplot
- Knows the theory, but has not applied it ANOVA test
- Knows the theory, but has not applied it T-statistic
- Knows the theory, but has not applied it Heatmaps
- Knows the theory, but has not applied it Writing a presentation
- Knows the theory, but has not applied it Go
- Applies in work, refers to documentation Network architecture
- Knows the theory, but has not applied it Cross-validation
- Applies in work, refers to documentation Learning rate
- Applies in work, refers to documentation Decomposition
- Applies in work, refers to documentation Deep web
- Applies in work, refers to documentation SQL
- Applies in work, refers to documentation Hadoop
- Knows the theory, but has not applied it Coef. Pearson, Spearman correlations
- Knows the theory, but has not applied it Markdown
- Knows the theory, but has not applied it Bar plot
- Knows the theory, but has not applied it Data normalization methods
- Knows the theory, but has not applied it Line plots
- Knows the theory, but has not applied it P-value and acceptable values
- Knows the theory, but has not applied it Metrics
- Applies in work, refers to documentation Models creation
- Knows the theory, but has not applied it Python
- Applies in work, refers to documentation The matrix
- Applies in work, refers to documentation language processing
- Applies in work, refers to documentation Time series
- Applies in work, refers to documentation Cosine/Euclidean distances
- Applies in work, refers to documentation Regularization
- Applies in work, refers to documentation Document categorization
- Applies in work, refers to documentation Probability theory
- Applies in work, refers to documentation Spark cluster
- Knows the theory, but has not applied it Histogram
- Knows the theory, but has not applied it Scatter plots
- Knows the theory, but has not applied it Calculation of mean/median/mode/variance/coefficient. variations
- Knows the theory, but has not applied it Dbscan
- Knows the theory, but has not applied it Bottom-up/Top-down approaches
- Applies in work, refers to documentation Generating features from text
- Applies in work, refers to documentation Algorithms
- Knows the theory, but has not applied it Countplot
- Applies in work, refers to documentation Gradient descent
- Applies in work, refers to documentation Activation types
- Knows the theory, but has not applied it Libraries
- Applies in work, refers to documentation Build quickly and iterate principles
- Applies in work, refers to documentation PCA/t-SNE
- Applies in work, refers to documentation Analysis

## Senior Data Analyst

### Skills needed for Senior Data Analyst

- Applies in work, refers to documentation Algorithms
- Knows the theory, but has not applied it K-means
- Knows the theory, but has not applied it Dbscan
- Knows the theory, but has not applied it Boxplot
- Applies in work, refers to documentation Activation types
- Applies in work, refers to documentation The matrix
- Applies in work, refers to documentation Build quickly and iterate principles
- Knows the theory, but has not applied it Python
- Applies in work, refers to documentation Analysis
- Applies in work, refers to documentation PCA/t-SNE
- Knows the theory, but has not applied it T-statistic
- Knows the theory, but has not applied it Metrics
- Knows the theory, but has not applied it Bar plot
- Knows the theory, but has not applied it Coef. Pearson, Spearman correlations
- Knows the theory, but has not applied it Scatter plots
- Knows the theory, but has not applied it Data normalization methods
- Applies in work, refers to documentation Time series
- Knows the theory, but has not applied it Cross-validation
- Applies in work, refers to documentation Document categorization
- Applies in work, refers to documentation Hadoop
- Confidently applies without reference to documentation Filters/Padding/Stride
- Confidently applies without reference to documentation Drawing a sample for deep learning
- Knows the theory, but has not applied it Calculation of mean/median/mode/variance/coefficient. variations
- Knows the theory, but has not applied it Hierarchical
- Knows the theory, but has not applied it Markdown
- Applies in work, refers to documentation Learning rate
- Knows the theory, but has not applied it Heatmaps
- Knows the theory, but has not applied it Bottom-up/Top-down approaches
- Applies in work, refers to documentation Gradient descent
- Applies in work, refers to documentation Regularization
- Applies in work, refers to documentation Network architecture
- Knows the theory, but has not applied it Go
- Applies in work, refers to documentation Generating features from text
- Applies in work, refers to documentation language processing
- Applies in work, refers to documentation SQL
- Applies in work, refers to documentation Decomposition
- Confidently applies without reference to documentation Convolution/Poolings
- Confidently applies without reference to documentation Convolutional networks
- Confidently applies without reference to documentation Transfer learning
- Confidently applies without reference to documentation RNN / LSTM / GRU
- Confidently applies without reference to documentation Collaborative filtering
- Confidently applies without reference to documentation Bayesian statistics
- Knows the theory, but has not applied it P-value and acceptable values
- Knows the theory, but has not applied it ANOVA test
- Knows the theory, but has not applied it Countplot
- Applies in work, refers to documentation Deep web
- Knows the theory, but has not applied it Line plots
- Knows the theory, but has not applied it Writing a presentation
- Applies in work, refers to documentation Models creation
- Knows the theory, but has not applied it Histogram
- Applies in work, refers to documentation Cosine/Euclidean distances
- Knows the theory, but has not applied it Libraries
- Confidently applies without reference to documentation Recurrent networks
- Applies in work, refers to documentation Spark cluster
- Applies in work, refers to documentation Probability theory
- Confidently applies without reference to documentation Models based on users and products

## Tech Lead Data Analyst

### Skills needed for Tech Lead Data Analyst

- Knows the theory, but has not applied it P-value and acceptable values
- Applies in work, refers to documentation Algorithms
- Knows the theory, but has not applied it Line plots
- Knows the theory, but has not applied it T-statistic
- Knows the theory, but has not applied it Countplot
- Applies in work, refers to documentation Network architecture
- Knows the theory, but has not applied it Python
- Applies in work, refers to documentation language processing
- Applies in work, refers to documentation The matrix
- Applies in work, refers to documentation Learning rate
- Knows the theory, but has not applied it Cross-validation
- Confidently applies without reference to documentation Models based on users and products
- Teaches others Reinforcement learning
- Knows the theory, but has not applied it Coef. Pearson, Spearman correlations
- Knows the theory, but has not applied it Histogram
- Knows the theory, but has not applied it K-means
- Applies in work, refers to documentation Regularization
- Applies in work, refers to documentation SQL
- Applies in work, refers to documentation Activation types
- Knows the theory, but has not applied it Libraries
- Confidently applies without reference to documentation Recurrent networks
- Applies in work, refers to documentation Hadoop
- Applies in work, refers to documentation Document categorization
- Knows the theory, but has not applied it Boxplot
- Knows the theory, but has not applied it Bar plot
- Knows the theory, but has not applied it ANOVA test
- Knows the theory, but has not applied it Markdown
- Knows the theory, but has not applied it Bottom-up/Top-down approaches
- Knows the theory, but has not applied it Dbscan
- Knows the theory, but has not applied it Hierarchical
- Knows the theory, but has not applied it Metrics
- Knows the theory, but has not applied it Data normalization methods
- Knows the theory, but has not applied it Heatmaps
- Applies in work, refers to documentation Models creation
- Knows the theory, but has not applied it Writing a presentation
- Applies in work, refers to documentation Spark cluster
- Applies in work, refers to documentation Cosine/Euclidean distances
- Confidently applies without reference to documentation RNN / LSTM / GRU
- Applies in work, refers to documentation PCA/t-SNE
- Applies in work, refers to documentation Probability theory
- Teaches others Discriminator/Generator
- Teaches others Generic Adversarial Networks
- Confidently applies without reference to documentation Transfer learning
- Applies in work, refers to documentation Build quickly and iterate principles
- Applies in work, refers to documentation Analysis
- Confidently applies without reference to documentation Drawing a sample for deep learning
- Confidently applies without reference to documentation Filters/Padding/Stride
- Knows the theory, but has not applied it Scatter plots
- Applies in work, refers to documentation Gradient descent
- Applies in work, refers to documentation Deep web
- Applies in work, refers to documentation Decomposition
- Applies in work, refers to documentation Time series
- Knows the theory, but has not applied it Go
- Confidently applies without reference to documentation Collaborative filtering
- Confidently applies without reference to documentation Convolution/Poolings
- Confidently applies without reference to documentation Convolutional networks
- Applies in work, refers to documentation Generating features from text
- Confidently applies without reference to documentation Bayesian statistics

Career Path

Junior Data Analyst

Middle Data Analyst

Senior Data Analyst

Tech Lead Data Analyst