Skills & Competencies for Data Science Manager

Data Science Manager job profile

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%
$160,818
TOTAL 50%
$179,993
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.

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)
Explains the importance and function 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 selection and implementation of big data platform technologies.
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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)
Explains the functions of existing and emerging data and business intelligence platforms.
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Level 2 Behaviors
(Light Experience)
Gathers business intelligence data to make informed conclusions on business practices.
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Level 3 Behaviors
(Moderate Experience)
Produces a user manual for the business intelligence system to assist stakeholders with proper data navigation.
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Level 4 Behaviors
(Extensive Experience)
Manages the overall data transformation from multiple sources into actionable business intelligence.
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Level 5 Behaviors
(Mastery)
Designs a new strategy for business intelligence insights to support our business's objectives.
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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)
Explains a specific technology and its application.
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Level 2 Behaviors
(Light Experience)
Responds to clients' inquiries regarding technology domains in a timely and efficient manner.
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Level 3 Behaviors
(Moderate Experience)
Uses data analytics to advise improvements on technology systems.
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Level 4 Behaviors
(Extensive Experience)
Leverages technology advising to provide accurate recommendations and solutions to technology needs.
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Level 5 Behaviors
(Mastery)
Establishes the policies and standard procedures for conducting our technology advising strategies.
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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)
Explains the importance of planning and organization in building a good working environment.
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Level 2 Behaviors
(Light Experience)
Identifies key implications of ineffective planning and organization that affects decision-making.
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Level 3 Behaviors
(Moderate Experience)
Leverages key performance indicators to measure progress completion against performance metrics.
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Level 4 Behaviors
(Extensive Experience)
Manages the planning and sequencing of activities to create well-planned schedules and achieve goals on time.
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Level 5 Behaviors
(Mastery)
Establishes standards for planning and organization processes to align efforts with business goals.
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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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