Development vector career path for 📈Data Science Developer

Junior 📈Data Science Developer

Skills needed for Junior 📈Data Science Developer

• Knows Demonstrate knowledge of inferential statistics
• Knows Demonstrate ability to manipulate, transform, and clean data
• Knows Demonstrate use of methodologies in the execution of the analytics cycle
• Knows Demonstrate understanding of model validation and selection techniques
• Knows Understand sampling, probability theory, and probability distributions
• Knows Demonstrate through a project the ability to analyze a dataset and communicate insights
• Knows Demonstrate knowledge of Python programming skills
• Knows Demonstrate knowledge of descriptive statistical concepts
• Knows Implement descriptive and inferential statistics using Python
• Knows Demonstrate ability to identify and collect data – multiple formats
• Learns Demonstrate through a project the ability to deploy and use a deployed model
• Knows Demonstrate ability to characterize a business problem
• Knows Demonstrate understanding of different modeling techniques
• Knows Communicate results translating insight into business value
• Knows Demonstrate through a project the ability to test different models on a dataset, validate and select the best model, and communicate results
• Knows Demonstrate ability to visualize data and extract insights
• Knows Demonstrate expertise with techniques to deal with missing values, outliers, unbalanced data, as well as data normalization
• Learns Deploy and monitor a validated model in an operational environment
• Knows Demonstrate through a project expertise with big data platforms (Hadoop, Spark)
• Knows Understand with the big data ecosystem and its major components
• Knows Demonstrate through a project the ability to plan for the execution of a project
• Knows Demonstrate understanding of what is data science and what data scientists do
• Knows Demonstrate understanding of Linear Algebra principles for machine learning
• Knows Demonstrate through a project the ability to construct usable data sets
• Knows Understand the concept of big data, and how big data is used at organizations
• Knows Demonstrate ability to formulate a business problem as a hypothesis question

Middle 📈Data Science Developer

Skills needed for Middle 📈Data Science Developer

• Helps Demonstrate through a project the ability to construct usable data sets
• Helps Demonstrate ability to manipulate, transform, and clean data
• Helps Demonstrate knowledge of inferential statistics
• Helps Demonstrate knowledge of descriptive statistical concepts
• Helps Demonstrate through a project the ability to plan for the execution of a project
• Helps Demonstrate understanding of what is data science and what data scientists do
• Helps Demonstrate understanding of different modeling techniques
• Helps Demonstrate understanding of Linear Algebra principles for machine learning
• Helps Demonstrate through a project the ability to test different models on a dataset, validate and select the best model, and communicate results
• Helps Demonstrate understanding of model validation and selection techniques
• Helps Communicate results translating insight into business value
• Does Demonstrate through a project the ability to deploy and use a deployed model
• Does Demonstrate through a project expertise with big data platforms (Hadoop, Spark)
• Does Understand the concept of big data, and how big data is used at organizations
• Does Understand with the big data ecosystem and its major components
• Helps Demonstrate through a project the ability to analyze a dataset and communicate insights
• Helps Demonstrate ability to characterize a business problem
• Helps Demonstrate use of methodologies in the execution of the analytics cycle
• Does Deploy and monitor a validated model in an operational environment
• Helps Demonstrate ability to identify and collect data – multiple formats
• Helps Demonstrate expertise with techniques to deal with missing values, outliers, unbalanced data, as well as data normalization
• Helps Understand sampling, probability theory, and probability distributions
• Helps Demonstrate knowledge of Python programming skills
• Helps Implement descriptive and inferential statistics using Python
• Helps Demonstrate ability to visualize data and extract insights
• Helps Demonstrate ability to formulate a business problem as a hypothesis question

Senior 📈Data Science Developer

Skills needed for Senior 📈Data Science Developer

• Mentors Demonstrate through a project the ability to analyze a dataset and communicate insights
• Mentors Demonstrate ability to visualize data and extract insights
• Mentors Understand the concept of big data, and how big data is used at organizations
• Mentors Demonstrate ability to manipulate, transform, and clean data
• Mentors Demonstrate through a project the ability to plan for the execution of a project
• Mentors Demonstrate knowledge of Python programming skills
• Mentors Demonstrate through a project expertise with big data platforms (Hadoop, Spark)
• Mentors Demonstrate through a project the ability to construct usable data sets
• Mentors Demonstrate ability to characterize a business problem
• Mentors Demonstrate ability to formulate a business problem as a hypothesis question
• Mentors Demonstrate use of methodologies in the execution of the analytics cycle
• Mentors Demonstrate understanding of different modeling techniques
• Mentors Demonstrate understanding of model validation and selection techniques
• Mentors Demonstrate understanding of Linear Algebra principles for machine learning
• Mentors Communicate results translating insight into business value
• Mentors Demonstrate through a project the ability to test different models on a dataset, validate and select the best model, and communicate results
• Mentors Demonstrate knowledge of descriptive statistical concepts
• Mentors Understand with the big data ecosystem and its major components
• Mentors Demonstrate through a project the ability to deploy and use a deployed model
• Mentors Deploy and monitor a validated model in an operational environment
• Mentors Demonstrate understanding of what is data science and what data scientists do
• Mentors Understand sampling, probability theory, and probability distributions
• Mentors Demonstrate knowledge of inferential statistics
• Mentors Implement descriptive and inferential statistics using Python
• Mentors Demonstrate ability to identify and collect data – multiple formats
• Mentors Demonstrate expertise with techniques to deal with missing values, outliers, unbalanced data, as well as data normalization

Tech Lead 📈Data Science Developer

Skills needed for Tech Lead 📈Data Science Developer

• Helps Demonstrate through a project expertise with big data platforms (Hadoop, Spark)
• Helps Understand with the big data ecosystem and its major components
• Helps Understand the concept of big data, and how big data is used at organizations
• Helps Demonstrate ability to formulate a business problem as a hypothesis question
• Helps Demonstrate use of methodologies in the execution of the analytics cycle
• Helps Demonstrate understanding of what is data science and what data scientists do
• Helps Demonstrate through a project the ability to analyze a dataset and communicate insights
• Helps Demonstrate understanding of Linear Algebra principles for machine learning
• Helps Demonstrate through a project the ability to plan for the execution of a project
• Helps Demonstrate ability to visualize data and extract insights
• Helps Demonstrate through a project the ability to construct usable data sets
• Helps Demonstrate understanding of model validation and selection techniques
• Helps Demonstrate through a project the ability to test different models on a dataset, validate and select the best model, and communicate results
• Helps Demonstrate ability to characterize a business problem
• Helps Understand sampling, probability theory, and probability distributions
• Helps Demonstrate knowledge of inferential statistics
• Helps Demonstrate knowledge of Python programming skills
• Helps Demonstrate knowledge of descriptive statistical concepts
• Helps Demonstrate through a project the ability to deploy and use a deployed model
• Helps Deploy and monitor a validated model in an operational environment
• Helps Demonstrate understanding of different modeling techniques
• Helps Communicate results translating insight into business value
• Helps Implement descriptive and inferential statistics using Python
• Helps Demonstrate ability to identify and collect data – multiple formats
• Helps Demonstrate expertise with techniques to deal with missing values, outliers, unbalanced data, as well as data normalization
• Helps Demonstrate ability to manipulate, transform, and clean data