Skills & Competencies for Data Science Manager

Data Science Manager job profile

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JOB SUMMARY for Data Science Manager

Manages the identification and utilization of large data sets to identify trends, patterns, and provide key business insights.

JOB RESPONSIBILITIES for Data Science Manager

Oversees and promotes data mining, cleaning, and aggregation processes and frameworks to prepare data, implement data models, conduct analysis, and develop databases. Coordinates the design and implementation of big data solutions for an organization, collaborating and liaising with stakeholders to ensure needs are captured. Provides technical guidance to evaluate data models, review code, and source data pipelines. Prioritizes tasks and allocates resources effectively to ensure timely delivery of projects. Builds team capability with mentoring, coaching, and professional development.

Data Science Manager SALARY RANGE

BASE 50%
$169,917
TOTAL 50%
$186,744
Job Level
M02
Job Code
IT10000563
Education/Degree
Master's Degree or MBA
Reports To
Director

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)
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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