Data Analyst
levels description
in 2022
Looking for Data Analyst levels description? This is an ultimate list of levels description for Data Analyst.
Individual Contributor (IC) career path for Data Analyst
Intern Data Analyst
Has less than 1 year of experience. Learning basic of design.
Skills needed for Intern Data Analyst
- Learns Algorithms
- Learns Deep web
- Learns Recurrent networks
- Learns Metrics
- Learns Network architecture
- Learns Decomposition
- Learns Generic Adversarial Networks
- Learns Discriminator/Generator
- Learns Regularization
- Learns Filters/Padding/Stride
- Learns Reinforcement learning
- Learns Gradient descent
- Learns The matrix
- Learns Convolution/Poolings
- Learns Time series
- Learns RNN / LSTM / GRU
- Learns Learning rate
- Learns Activation types
- Learns Convolutional networks
- Learns Models based on users and products
- Learns Collaborative filtering
- Learns Recommender systems
- Learns K-means
- Learns Language processing
- Learns Cosine/Euclidean distances
- Learns Dbscan
- Learns Hierarchical
- Learns Generating features from text
- Learns Document categorization
- Learns PCA/t-SNE
- Learns P-value and acceptable values
- Learns T-statistic
- Learns Bayesian statistics
- Learns Calculation of mean/median/mode/variance/coefficient. variations
- Learns ANOVA test
- Learns Probability theory
- Learns Coef. Pearson, Spearman correlations
- Learns Transfer learning
- Learns Analysis
- Learns Cross-validation
- Learns Data normalization methods
- Learns Drawing a sample for deep learning
- Learns Models creation
- Learns Markdown
- Learns Build quickly and iterate principles
- Learns Writing a presentation
- Learns Bottom-up/Top-down approaches
- Learns Libraries
- Learns Python
- Learns Go
- Learns Hadoop
- Learns Spark cluster
- Learns Development process
- Learns Scrum
- Learns Completing tasks
- Learns Teamwork
- Learns TDD
- Learns Scrumban
- Learns Kanban
- Learns Fault tolerance. The maximum number of requests to process (rps)
Junior Data Analyst
Has approximately 1-2 years experience and basic design foundations. Contribute ideas during team meetings
Skills needed for Junior Data Analyst
- Knows Models based on users and products
- Knows Collaborative filtering
- Knows Recommender systems
- Knows K-means
- Knows Language processing
- Knows Cosine/Euclidean distances
- Knows Dbscan
- Knows Hierarchical
- Knows Generating features from text
- Knows Document categorization
- Knows PCA/t-SNE
- Knows Algorithms
- Knows Deep web
- Knows Recurrent networks
- Knows Metrics
- Knows Network architecture
- Knows Decomposition
- Knows Generic Adversarial Networks
- Knows Discriminator/Generator
- Knows Regularization
- Knows Filters/Padding/Stride
- Knows Reinforcement learning
- Knows Gradient descent
- Knows The matrix
- Knows Convolution/Poolings
- Knows Time series
- Knows RNN / LSTM / GRU
- Knows Learning rate
- Knows Activation types
- Knows Convolutional networks
- Learns P-value and acceptable values
- Learns T-statistic
- Learns Bayesian statistics
- Learns Calculation of mean/median/mode/variance/coefficient. variations
- Learns ANOVA test
- Learns Probability theory
- Learns Coef. Pearson, Spearman correlations
- Learns Markdown
- Learns Build quickly and iterate principles
- Learns Writing a presentation
- Learns Bottom-up/Top-down approaches
- Knows Transfer learning
- Knows Analysis
- Knows Cross-validation
- Knows Data normalization methods
- Knows Drawing a sample for deep learning
- Knows Models creation
- Knows Hadoop
- Knows Spark cluster
- Knows Libraries
- Knows Python
- Knows Go
- Learns Development process
- Learns Scrum
- Learns Completing tasks
- Learns Teamwork
- Learns TDD
- Learns Scrumban
- Learns Kanban
- Learns Fault tolerance. The maximum number of requests to process (rps)
- Learns SQL
- Learns Countplot
- Learns Heatmaps
- Learns Boxplot
- Learns Histogram
- Learns Line plots
- Learns Bar plot
- Learns Scatter plots
Middle Data Analyst
Has more than 2 years of experience in design. They need less supervision and minimal reworks.<br/><br/>
Skills needed for Middle Data Analyst
- Knows Models based on users and products
- Knows Collaborative filtering
- Knows Recommender systems
- Knows K-means
- Knows Language processing
- Knows Cosine/Euclidean distances
- Knows Dbscan
- Knows Hierarchical
- Knows Generating features from text
- Knows Document categorization
- Knows PCA/t-SNE
- Knows P-value and acceptable values
- Knows T-statistic
- Knows Bayesian statistics
- Knows Calculation of mean/median/mode/variance/coefficient. variations
- Knows ANOVA test
- Knows Probability theory
- Knows Coef. Pearson, Spearman correlations
- Learns Transfer learning
- Learns Analysis
- Learns Cross-validation
- Learns Data normalization methods
- Learns Drawing a sample for deep learning
- Learns Models creation
- Does Algorithms
- Does Deep web
- Does Recurrent networks
- Does Metrics
- Does Network architecture
- Does Decomposition
- Does Generic Adversarial Networks
- Does Discriminator/Generator
- Does Regularization
- Does Filters/Padding/Stride
- Does Reinforcement learning
- Does Gradient descent
- Does The matrix
- Does Convolution/Poolings
- Does Time series
- Does RNN / LSTM / GRU
- Does Learning rate
- Does Activation types
- Does Convolutional networks
- Does Development process
- Does Scrum
- Does Completing tasks
- Does Teamwork
- Does TDD
- Does Scrumban
- Does Kanban
- Does Fault tolerance. The maximum number of requests to process (rps)
- Learns Markdown
- Learns Build quickly and iterate principles
- Learns Writing a presentation
- Learns Bottom-up/Top-down approaches
- Knows Libraries
- Knows Python
- Knows Go
- Knows Hadoop
- Knows Spark cluster
- Learns SQL
- Learns Countplot
- Learns Heatmaps
- Learns Boxplot
- Learns Histogram
- Learns Line plots
- Learns Bar plot
- Learns Scatter plots
Senior Data Analyst
Create expert designs, take complex projects and mentor junior designers. They have 5-8 years of experience
Skills needed for Senior Data Analyst
- Does Transfer learning
- Does Analysis
- Does Cross-validation
- Does Data normalization methods
- Does Drawing a sample for deep learning
- Does Models creation
- Does Models based on users and products
- Does Collaborative filtering
- Does Recommender systems
- Does K-means
- Does Language processing
- Does Cosine/Euclidean distances
- Does Dbscan
- Does Hierarchical
- Does Generating features from text
- Does Document categorization
- Does PCA/t-SNE
- Does P-value and acceptable values
- Does T-statistic
- Does Bayesian statistics
- Does Calculation of mean/median/mode/variance/coefficient. variations
- Does ANOVA test
- Does Probability theory
- Does Coef. Pearson, Spearman correlations
- Helps Development process
- Helps Scrum
- Helps Completing tasks
- Helps Teamwork
- Helps TDD
- Helps Scrumban
- Helps Kanban
- Helps Fault tolerance. The maximum number of requests to process (rps)
- Helps Libraries
- Helps Python
- Helps Go
- Does Algorithms
- Does Deep web
- Does Recurrent networks
- Does Metrics
- Does Network architecture
- Does Decomposition
- Does Generic Adversarial Networks
- Does Discriminator/Generator
- Does Regularization
- Does Filters/Padding/Stride
- Does Reinforcement learning
- Does Gradient descent
- Does The matrix
- Does Convolution/Poolings
- Does Time series
- Does RNN / LSTM / GRU
- Does Learning rate
- Does Activation types
- Does Convolutional networks
- Learns Markdown
- Learns Build quickly and iterate principles
- Learns Writing a presentation
- Learns Bottom-up/Top-down approaches
- Knows Hadoop
- Knows Spark cluster
- Knows SQL
- Knows Countplot
- Knows Heatmaps
- Knows Boxplot
- Knows Histogram
- Knows Line plots
- Knows Bar plot
- Knows Scatter plots
Manager career path for Data Analyst
Design Manager / Design Lead Data Analyst
Has more than 7 years of experience. Rather than design, they take on the managerial responsibilities and DesignOps
Skills needed for Design Manager / Design Lead Data Analyst
- Does Algorithms
- Does Deep web
- Does Recurrent networks
- Does Metrics
- Does Network architecture
- Does Decomposition
- Does Generic Adversarial Networks
- Does Discriminator/Generator
- Does Regularization
- Does Filters/Padding/Stride
- Does Reinforcement learning
- Does Gradient descent
- Does The matrix
- Does Convolution/Poolings
- Does Time series
- Does RNN / LSTM / GRU
- Does Learning rate
- Does Activation types
- Does Convolutional networks
- Helps Models based on users and products
- Helps Collaborative filtering
- Helps Recommender systems
- Helps K-means
- Helps Language processing
- Helps Cosine/Euclidean distances
- Helps Dbscan
- Helps Hierarchical
- Helps Generating features from text
- Helps Document categorization
- Helps PCA/t-SNE
- Does P-value and acceptable values
- Does T-statistic
- Does Bayesian statistics
- Does Calculation of mean/median/mode/variance/coefficient. variations
- Does ANOVA test
- Does Probability theory
- Does Coef. Pearson, Spearman correlations
- Does SQL
- Does Countplot
- Does Heatmaps
- Does Boxplot
- Does Histogram
- Does Line plots
- Does Bar plot
- Does Scatter plots
- Does Transfer learning
- Does Analysis
- Does Cross-validation
- Does Data normalization methods
- Does Drawing a sample for deep learning
- Does Models creation
- Helps Markdown
- Helps Build quickly and iterate principles
- Helps Writing a presentation
- Helps Bottom-up/Top-down approaches
- Helps Libraries
- Helps Python
- Helps Go
- Does Hadoop
- Does Spark cluster
- Does Development process
- Does Scrum
- Does Completing tasks
- Does Teamwork
- Does TDD
- Does Scrumban
- Does Kanban
- Does Fault tolerance. The maximum number of requests to process (rps)
Art Director Data Analyst
Manages a larger team. Design leads report to the Art Director on team’s progress, setbacks, and other<br/>
Skills needed for Art Director Data Analyst
- Helps P-value and acceptable values
- Helps T-statistic
- Helps Bayesian statistics
- Helps Calculation of mean/median/mode/variance/coefficient. variations
- Helps ANOVA test
- Helps Probability theory
- Helps Coef. Pearson, Spearman correlations
- Does SQL
- Does Countplot
- Does Heatmaps
- Does Boxplot
- Does Histogram
- Does Line plots
- Does Bar plot
- Does Scatter plots
- Mentors Models based on users and products
- Mentors Collaborative filtering
- Mentors Recommender systems
- Mentors K-means
- Mentors Language processing
- Mentors Cosine/Euclidean distances
- Mentors Dbscan
- Mentors Hierarchical
- Mentors Generating features from text
- Mentors Document categorization
- Mentors PCA/t-SNE
- Does Transfer learning
- Does Analysis
- Does Cross-validation
- Does Data normalization methods
- Does Drawing a sample for deep learning
- Does Models creation
- Helps Libraries
- Helps Python
- Helps Go
- Helps Markdown
- Helps Build quickly and iterate principles
- Helps Writing a presentation
- Helps Bottom-up/Top-down approaches
- Helps Hadoop
- Helps Spark cluster
- Does Development process
- Does Scrum
- Does Completing tasks
- Does Teamwork
- Does TDD
- Does Scrumban
- Does Kanban
- Does Fault tolerance. The maximum number of requests to process (rps)
- Helps Algorithms
- Helps Deep web
- Helps Recurrent networks
- Helps Metrics
- Helps Network architecture
- Helps Decomposition
- Helps Generic Adversarial Networks
- Helps Discriminator/Generator
- Helps Regularization
- Helps Filters/Padding/Stride
- Helps Reinforcement learning
- Helps Gradient descent
- Helps The matrix
- Helps Convolution/Poolings
- Helps Time series
- Helps RNN / LSTM / GRU
- Helps Learning rate
- Helps Activation types
- Helps Convolutional networks
Design Director Data Analyst
Has 10+ years of experience and 5+ years of leading a team. Design director contributes to the R&D and product design strategy
Skills needed for Design Director Data Analyst
- Does SQL
- Does Countplot
- Does Heatmaps
- Does Boxplot
- Does Histogram
- Does Line plots
- Does Bar plot
- Does Scatter plots
- Helps P-value and acceptable values
- Helps T-statistic
- Helps Bayesian statistics
- Helps Calculation of mean/median/mode/variance/coefficient. variations
- Helps ANOVA test
- Helps Probability theory
- Helps Coef. Pearson, Spearman correlations
- Mentors Models based on users and products
- Mentors Collaborative filtering
- Mentors Recommender systems
- Mentors K-means
- Mentors Language processing
- Mentors Cosine/Euclidean distances
- Mentors Dbscan
- Mentors Hierarchical
- Mentors Generating features from text
- Mentors Document categorization
- Mentors PCA/t-SNE
- Helps Libraries
- Helps Python
- Helps Go
- Helps Transfer learning
- Helps Analysis
- Helps Cross-validation
- Helps Data normalization methods
- Helps Drawing a sample for deep learning
- Helps Models creation
- Helps Markdown
- Helps Build quickly and iterate principles
- Helps Writing a presentation
- Helps Bottom-up/Top-down approaches
- Mentors Hadoop
- Mentors Spark cluster
- Helps Development process
- Helps Scrum
- Helps Completing tasks
- Helps Teamwork
- Helps TDD
- Helps Scrumban
- Helps Kanban
- Helps Fault tolerance. The maximum number of requests to process (rps)
- Helps Algorithms
- Helps Deep web
- Helps Recurrent networks
- Helps Metrics
- Helps Network architecture
- Helps Decomposition
- Helps Generic Adversarial Networks
- Helps Discriminator/Generator
- Helps Regularization
- Helps Filters/Padding/Stride
- Helps Reinforcement learning
- Helps Gradient descent
- Helps The matrix
- Helps Convolution/Poolings
- Helps Time series
- Helps RNN / LSTM / GRU
- Helps Learning rate
- Helps Activation types
- Helps Convolutional networks
VP of Design Data Analyst
Has 10+ years of experience and 5+ years of leading a team. Design director contributes to the R&D and product design strategy
Skills needed for VP of Design Data Analyst
- Helps SQL
- Helps Countplot
- Helps Heatmaps
- Helps Boxplot
- Helps Histogram
- Helps Line plots
- Helps Bar plot
- Helps Scatter plots
- Helps P-value and acceptable values
- Helps T-statistic
- Helps Bayesian statistics
- Helps Calculation of mean/median/mode/variance/coefficient. variations
- Helps ANOVA test
- Helps Probability theory
- Helps Coef. Pearson, Spearman correlations
- Mentors Hadoop
- Mentors Spark cluster
- Mentors Transfer learning
- Mentors Analysis
- Mentors Cross-validation
- Mentors Data normalization methods
- Mentors Drawing a sample for deep learning
- Mentors Models creation
- Helps Libraries
- Helps Python
- Helps Go
- Helps Markdown
- Helps Build quickly and iterate principles
- Helps Writing a presentation
- Helps Bottom-up/Top-down approaches
- Helps Development process
- Helps Scrum
- Helps Completing tasks
- Helps Teamwork
- Helps TDD
- Helps Scrumban
- Helps Kanban
- Helps Fault tolerance. The maximum number of requests to process (rps)
- Mentors Models based on users and products
- Mentors Collaborative filtering
- Mentors Recommender systems
- Mentors K-means
- Mentors Language processing
- Mentors Cosine/Euclidean distances
- Mentors Dbscan
- Mentors Hierarchical
- Mentors Generating features from text
- Mentors Document categorization
- Mentors PCA/t-SNE
- Helps Algorithms
- Helps Deep web
- Helps Recurrent networks
- Helps Metrics
- Helps Network architecture
- Helps Decomposition
- Helps Generic Adversarial Networks
- Helps Discriminator/Generator
- Helps Regularization
- Helps Filters/Padding/Stride
- Helps Reinforcement learning
- Helps Gradient descent
- Helps The matrix
- Helps Convolution/Poolings
- Helps Time series
- Helps RNN / LSTM / GRU
- Helps Learning rate
- Helps Activation types
- Helps Convolutional networks
Individual Contributor (IC)
Intern Data Analyst
Junior Data Analyst
Middle Data Analyst
Senior Data Analyst
Manager
Design Manager / Design Lead Data Analyst
Art Director Data Analyst
Design Director Data Analyst
VP of Design Data Analyst
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