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%
$158,352
TOTAL 50%
$177,234
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)
Discusses the lifecycle phases of big data analytics.
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Level 2 Behaviors
(Light Experience)
Enters large amounts of data and reports into big data analytics tools.
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Level 3 Behaviors
(Moderate Experience)
Partners with senior management to deliver key analytic solutions using big data.
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Level 4 Behaviors
(Extensive Experience)
Interprets results of big data analytics research report to forecast product volume and supply in various regions.
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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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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 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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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)
Compiles a list of all the traits and characteristics of effective technology advising.
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Level 2 Behaviors
(Light Experience)
Applies the guidelines for conducting advice practices to help the continuous improvement of the business.
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Level 3 Behaviors
(Moderate Experience)
Participates in the development of new procedures for delivering technology advising services.
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Level 4 Behaviors
(Extensive Experience)
Drafts the guidelines for addressing issues on technology advising processes.
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Level 5 Behaviors
(Mastery)
Advocates for new tools and methods to innovate the process of our technology advising operations.
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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)
Compiles a list of all the traits of effective planning to help finish the assigned tasks.
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Level 2 Behaviors
(Light Experience)
Classifies assigned tasks based on the level of importance to ensure organized workload completion.
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Level 3 Behaviors
(Moderate Experience)
Defines and translates objectives into specific plans to ensure understanding of organizational goals.
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Level 4 Behaviors
(Extensive Experience)
Delivers training sessions to foster and maximize solid planning and organization capabilities.
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Level 5 Behaviors
(Mastery)
Champions the adoption of business intelligence systems to achieve planning and organization 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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