13 general skills or competencies (Job family competencies) for Data Science Manager
Skill definition-Collecting, analyzing, and interpreting a large amount of data to uncover information to help organizations make informed business decisions.
Level 1 Behaviors
(General Familiarity)
Discusses the lifecycle phases of big data analytics.
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Level 2 Behaviors
(Light Experience)
Gathers the department's requirements for efficient big data analytics.
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Level 3 Behaviors
(Moderate Experience)
Suggests effective approaches for big data analytics to support dashboard and report development.
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Level 4 Behaviors
(Extensive Experience)
Manages advanced and complex big data analytics based on the overall business needs.
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Level 5 Behaviors
(Mastery)
Leads the development of an information architecture framework for our data analytics platform.
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Skill definition-Evaluating business data, translating it to actionable insights, and using it to make better-informed decisions.
Level 1 Behaviors
(General Familiarity)
Explains the data modeling and reporting concepts applicable to business Intelligence.
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Level 2 Behaviors
(Light Experience)
Collects business intelligence data to analyze our business's competitiveness.
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Level 3 Behaviors
(Moderate Experience)
Partners with the management in streamlining business intelligence and analytics tools.
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Level 4 Behaviors
(Extensive Experience)
Drives the overall data quality improvement initiatives to leverage business intelligence tools.
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Level 5 Behaviors
(Mastery)
Creates overall solutions for various complex enterprise needs in the business intelligence area.
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11 soft skills or competencies (core competencies) for Data Science Manager
Skill definition-Applying advisory methods to deliver solutions for internal or external clients' technology needs.
Level 1 Behaviors
(General Familiarity)
Describes the key roles and responsibilities of a technical advisor.
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Level 2 Behaviors
(Light Experience)
Explains the features of a particular product or service in simple terms to the clients.
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Level 3 Behaviors
(Moderate Experience)
Provides guidance to others in advising various clients on technology solutions.
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Level 4 Behaviors
(Extensive Experience)
Evaluates emerging technologies and anticipates their potential business impacts.
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Level 5 Behaviors
(Mastery)
Develops advising materials to support our employees in dealing with technology needs.
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Skill definition-Managing and prioritizing resources and workloads by creating well-organized plans to attain organizational goals and objectives.
Level 1 Behaviors
(General Familiarity)
Documents best practices in planning and organizing work to address important tasks.
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Level 2 Behaviors
(Light Experience)
Discusses the positive and negative outcomes of planning and organization in the workplace.
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Level 3 Behaviors
(Moderate Experience)
Helps set up new practices to anticipate and address the needs of planning and organization initiatives.
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Level 4 Behaviors
(Extensive Experience)
Facilitates the adoption of advanced tools to streamline the process of planning and organization.
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Level 5 Behaviors
(Mastery)
Develops best practices in planning and organizing activities to improve organizational efficiency.
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Summary of Data Science Manager skills and competencies
There are 0 hard skills for Data Science Manager.
13 general skills for Data Science Manager, Big Data Analytics, Business Intelligence, Data Analytics, etc.
11 soft skills for Data Science Manager, Technology Advising, Planning and Organizing, Prioritization, etc.
While the list totals 24 distinct skills, it's important to note that not all are required to be mastered to the same degree. Some skills may only need a basic understanding, whereas others demand a higher level of expertise.
For instance, as a Data Science Manager, he or she needs to be skilled in Technology Advising, be skilled in Planning and Organizing, and be skilled in Prioritization.