Skills & Competencies for Data Science Manager

Data Science Manager job profile

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JOB SUMMARY for Data Science Manager

Manages teams tasked with identifying trends, patterns, and anomalies found in big data sets and used to develop insights by performing extensive data analysis.

JOB RESPONSIBILITIES for Data Science Manager

Oversees the interpretation of results from multiple sources using a variety of techniques, ranging from simple data aggregation via statistical analysis to complex data mining. Manages the design and implementation of big data solutions for the organization. Uses extensive knowledge and research into big data tools to guide data scientists' adoption and use of new and existing tools.

Data Science Manager SALARY RANGE

BASE 50%
$157,939
TOTAL 50%
$176,770
Job Level
M02
Job Code
IT10000563
Education/Degree
Master's Degree or MBA
Reports To
Senior Management

Data Science Manager Skills and Competencies List

Proficiency Levels and Behavioural Indicators
Salary.com identifies five increasing levels of proficiency for each skill/competency. Some jobs require only a relatively low level of proficiency in each skill/competency, while other jobs will require a more advanced level of proficiency in the same skill/competency. These levels rate the degree of proficiency (skill level, expertise) we expect the incumbent to perform in the given skill/competency for the given job. Note that we intentionally do not associate timeframes or years of experience in performing the skill/competency because that can be misleading. Proficiency levels identify what the incumbent knows and can do rather than how long they have been doing it. Also, note that the proficiency levels are cumulative, e.g., a level 4 proficiency implies the ability to perform all the behaviors at the lower levels.
Check each Data Science Manager skill and competencie below to view definitions.
JOB FAMILY COMPETENCIES CORE COMPETENCIES
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13 general skills or competencies (Job family competencies) for Data Science Manager

1 Job Family Competencies – Big Data Analytics
Proficiency Level -4
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.
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Level 2 Behaviors
(Light Experience)
Assists in extracting, reviewing, and outlining relevant data from systems.
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Level 3 Behaviors
(Moderate Experience)
Consults on the application of big data models and analytics tools to support the development of innovative solutions.
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Level 4 Behaviors
(Extensive Experience)
Delivers actionable insight and highly informative measurements for big data analytics.
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Level 5 Behaviors
(Mastery)
Champions the adoption of advanced software to support the management and processing of data sets.
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2 Job Family Competencies – Business Intelligence
Proficiency Level -3
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.
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Level 2 Behaviors
(Light Experience)
Assists in developing enterprise business intelligence applications to collect large amounts of data.
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Level 3 Behaviors
(Moderate Experience)
Implements complex analysis solutions to support the business intelligence environment.
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Level 4 Behaviors
(Extensive Experience)
Aligns the business capability requirements to the business intelligence and data strategy roadmaps.
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Level 5 Behaviors
(Mastery)
Champions the adoption of advanced business intelligence tools to promote the data dissemination process.
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3 Data Science Manager - Skill and Competency
Proficiency Level - 3
4 Skill and Competency - Data Science Manager
Proficiency Level - 4
5 Competency for - Data Science Manager
Proficiency Level - 5

11 soft skills or competencies (core competencies) for Data Science Manager

1 Core Competencies – Technology Advising
Proficiency Level -3
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.
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Level 2 Behaviors
(Light Experience)
Advises clients regarding the products, technologies and services based on their business needs.
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Level 3 Behaviors
(Moderate Experience)
Effectively conveys technology concepts and business impacts to senior client levels.
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Level 4 Behaviors
(Extensive Experience)
Delivers training on procedures for conducting technology advising in our workplace.
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Level 5 Behaviors
(Mastery)
Adapts the latest trends in processes and computer skills relevant to technology advising.
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2 Core Competencies – Planning and Organizing
Proficiency Level -3
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.
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Level 2 Behaviors
(Light Experience)
Assists in identifying and breaking tasks into a sequence of steps for a more organized task plan.
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Level 3 Behaviors
(Moderate Experience)
Aligns tasks and priorities with business goals and objectives.
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Level 4 Behaviors
(Extensive Experience)
Creates programs to improve planning and organization of work to achieve business objectives.
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Level 5 Behaviors
(Mastery)
Builds and designs organizational systems and planning tools to enhance overall productivity.
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3 Data Science Manager - Skill and Competency
Proficiency Level - 3
4 Skill and Competency - Data Science Manager
Proficiency Level - 4
5 Competency for - Data Science Manager
Proficiency Level - 5

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.

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