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)
Lists commonly used analytic tools, techniques, and methods.
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Level 2 Behaviors
(Light Experience)
Supports in-memory processing to boost the performance of big data analytic applications.
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Level 3 Behaviors
(Moderate Experience)
Utilizes big data analytics tools for data retrieval, preparation, and modeling.
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Level 4 Behaviors
(Extensive Experience)
Provides expert analysis and recommendations on current and emerging approaches for big data analytics.
See 4 More Skill Behaviors
Level 5 Behaviors
(Mastery)
Oversees the big data analytics pipeline development to optimize the entire process.
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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)
Lists the basic features of general business intelligence systems and database structure.
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Level 2 Behaviors
(Light Experience)
Supports end-users in using business intelligence tools to query databases for outputs and data preparation.
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Level 3 Behaviors
(Moderate Experience)
Utilizes business intelligence platforms to derive insights to present the data to our business.
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Level 4 Behaviors
(Extensive Experience)
Provides technical oversight and design to support the development of business intelligence solutions.
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Level 5 Behaviors
(Mastery)
Leads the development of visual business intelligence models to utilize business intelligence tools.
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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)
Lists the basic obstacles, challenges, and potential problems in technology advising.
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Level 2 Behaviors
(Light Experience)
Supports management for formulating advising solutions to address basic business issues.
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Level 3 Behaviors
(Moderate Experience)
Utilizes technology advising tools to identify and provide interventions for technology issues.
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Level 4 Behaviors
(Extensive Experience)
Provides advice for continuous improvement to integrate our technology and improve our processes.
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Level 5 Behaviors
(Mastery)
Leads in developing and implementing technology advising tools to optimize functions in our workplace.
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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)
Lists commonly used tools in workplace planning and organization.
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Level 2 Behaviors
(Light Experience)
Works with specific tools in prioritizing and allocating resources to ensure task accuracy.
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Level 3 Behaviors
(Moderate Experience)
Prepares schedules to plan, organize, and complete priorities promptly.
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Level 4 Behaviors
(Extensive Experience)
Sets short- and long-term objectives to organize team workload and improve efficiency.
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Level 5 Behaviors
(Mastery)
Leads the development of new techniques and strategies to drive effective planning and organization.
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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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