Skills & Competencies for Data Science Director

Data Science Director job profile

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JOB SUMMARY for Data Science Director

Establishes, plans, and administers the overall policies and goals of the data science function.

JOB RESPONSIBILITIES for Data Science Director

Provides strategic guidance and overall direction for analytical efforts. Determines the appropriate tools, techniques, staffing and methodologies to extract data that produces meaningful results. Uses extensive knowledge and research into big data tools to guide the integration of new and existing tools into the organization’s data science tech stack.

Data Science Director SALARY RANGE

BASE 50%
$200,881
TOTAL 50%
$235,034
Job Level
M04
Job Code
EX05000338
Education/Degree
Master's Degree or MBA
Reports To
Top Management

Data Science Director 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 Director skill and competencie below to view definitions.
JOB FAMILY COMPETENCIES CORE COMPETENCIES
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10 general skills or competencies (Job family competencies) for Data Science Director

1 Job Family Competencies – Big Data Analytics
Proficiency Level -3
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 Director - Skill and Competency
Proficiency Level - 3
4 Skill and Competency - Data Science Director
Proficiency Level - 4
5 Competency for - Data Science Director
Proficiency Level - 5

10 soft skills or competencies (core competencies) for Data Science Director

1 Core Competencies – Business Acumen
Proficiency Level -3
Skill definition-Insight into our organization's business, goals, and values. Ability to design and implement initiatives that facilitate successful outcomes.
Level 1 Behaviors
(General Familiarity)
Describes how our business makes money and our key business objectives.
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Level 2 Behaviors
(Light Experience)
Assists in designing business models and operating plans.
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Level 3 Behaviors
(Moderate Experience)
Analyses the business impact of demographic changes; suggests effective responses.
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Level 4 Behaviors
(Extensive Experience)
Consults on the selection and adjustment of the go-to-market strategy.
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Level 5 Behaviors
(Mastery)
Builds a mentoring model to ensure a continuous increase of business sense within our business.
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2 Core Competencies – Technology Advising
Proficiency Level -4
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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3 Data Science Director - Skill and Competency
Proficiency Level - 3
4 Skill and Competency - Data Science Director
Proficiency Level - 4
5 Competency for - Data Science Director
Proficiency Level - 5

Summary of Data Science Director skills and competencies

There are 0 hard skills for Data Science Director.
10 general skills for Data Science Director, Big Data Analytics, Business Intelligence, Data Analytics, etc.
10 soft skills for Data Science Director, Business Acumen, Technology Advising, Planning and Organizing, etc.
While the list totals 20 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 Director, he or she needs to be skilled in Business Acumen, be skilled in Technology Advising, and be an expert in Planning and Organizing.

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