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)
Cites examples of the different methods used in big data analytics.
See 4 More Skill Behaviors
Level 2 Behaviors
(Light Experience)
Assists in extracting, reviewing, and outlining relevant data from systems.
See 4 More Skill Behaviors
Level 3 Behaviors
(Moderate Experience)
Consults on the application of big data models and analytics tools to support the development of innovative solutions.
See 4 More Skill Behaviors
Level 4 Behaviors
(Extensive Experience)
Delivers actionable insight and highly informative measurements for big data analytics.
See 4 More Skill Behaviors
Level 5 Behaviors
(Mastery)
Champions the adoption of advanced software to support the management and processing of data sets.
See 4 More Skill Behaviors
Skill definition-Evaluating business data, translating it to actionable insights, and using it to make better-informed decisions.
Level 1 Behaviors
(General Familiarity)
Compiles a list of the basic processes to navigate business intelligence dashboards and tools.
See 4 More Skill Behaviors
Level 2 Behaviors
(Light Experience)
Assists in developing enterprise business intelligence applications to collect large amounts of data.
See 4 More Skill Behaviors
Level 3 Behaviors
(Moderate Experience)
Implements complex analysis solutions to support the business intelligence environment.
See 4 More Skill Behaviors
Level 4 Behaviors
(Extensive Experience)
Aligns the business capability requirements to the business intelligence and data strategy roadmaps.
See 4 More Skill Behaviors
Level 5 Behaviors
(Mastery)
Champions the adoption of advanced business intelligence tools to promote the data dissemination process.
See 4 More Skill Behaviors
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)
Cites the commonly used technology advising tools in our workplace.
See 4 More Skill Behaviors
Level 2 Behaviors
(Light Experience)
Advises clients regarding the products, technologies and services based on their business needs.
See 4 More Skill Behaviors
Level 3 Behaviors
(Moderate Experience)
Effectively conveys technology concepts and business impacts to senior client levels.
See 4 More Skill Behaviors
Level 4 Behaviors
(Extensive Experience)
Delivers training on procedures for conducting technology advising in our workplace.
See 4 More Skill Behaviors
Level 5 Behaviors
(Mastery)
Adapts the latest trends in processes and computer skills relevant to technology advising.
See 4 More Skill Behaviors
Skill definition-Managing and prioritizing resources and workloads by creating well-organized plans to attain organizational goals and objectives.
Level 1 Behaviors
(General Familiarity)
Cites potential challenges and workplace issues in delegating tasks that may impede well coordinated work.
See 4 More Skill Behaviors
Level 2 Behaviors
(Light Experience)
Assists in identifying and breaking tasks into a sequence of steps for a more organized task plan.
See 4 More Skill Behaviors
Level 3 Behaviors
(Moderate Experience)
Aligns tasks and priorities with business goals and objectives.
See 4 More Skill Behaviors
Level 4 Behaviors
(Extensive Experience)
Creates programs to improve planning and organization of work to achieve business objectives.
See 4 More Skill Behaviors
Level 5 Behaviors
(Mastery)
Builds and designs organizational systems and planning tools to enhance overall productivity.
See 4 More Skill Behaviors
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.