Skills & Competencies for Data Scientist I

Data Scientist I job profile

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JOB SUMMARY for Data Scientist I

Identifies trends, patterns, and anomalies found in big data sets by performing extensive data analysis to develop insights.

JOB RESPONSIBILITIES for Data Scientist I

Performs data mining, cleaning, and aggregation processes to prepare data, implement data models, conduct analysis, and develop databases. Interprets results from multiple structured and unstructured data sources using programming, statistical, and analytical techniques and tools. Collaborates with teams to understand each data analysis projects' underlying purpose, focus, and objectives. Designs, develops, and implements the most valuable data-driven solutions for the organization.

Data Scientist I SALARY RANGE

BASE 50%
$77,302
TOTAL 50%
$79,542
Job Level
P01
Job Code
IT10000546
Education/Degree
Master's Degree or MBA
Reports To
Manager

Data Scientist I 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 Scientist I skill and competencie below to view definitions.
JOB FAMILY COMPETENCIES CORE COMPETENCIES
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18 general skills or competencies (Job family competencies) for Data Scientist I

1 Job Family Competencies – Big Data Analytics
Proficiency Level -2
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)
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 development of an information architecture framework for our data analytics platform.
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2 Job Family Competencies – Business Intelligence
Proficiency Level -2
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 Scientist I - Skill and Competency
Proficiency Level - 3
4 Skill and Competency - Data Scientist I
Proficiency Level - 4
5 Competency for - Data Scientist I
Proficiency Level - 5

6 soft skills or competencies (core competencies) for Data Scientist I

1 Core Competencies – Business Acumen
Proficiency Level -1
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)
Names our key stakeholders from a business value chain perspective.
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Level 2 Behaviors
(Light Experience)
Supports the planning, implementation, and management of training programs that foster process improvements.
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Level 3 Behaviors
(Moderate Experience)
Participates in the redesign of organizational structures to reflect business priorities.
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Level 4 Behaviors
(Extensive Experience)
Trains others on various business and operation topics.
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Level 5 Behaviors
(Mastery)
Forecasts the short-term and long-term impact of various business cases on P&L performance.
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2 Core Competencies – Predictive Analytics
Proficiency Level -2
Skill definition-Gathering, analyzing, and predicting patterns and structures of historical data and trends to make strategic decisions for better future outcomes.
Level 1 Behaviors
(General Familiarity)
Lists various kinds of applications that use predictive analytics.
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Level 2 Behaviors
(Light Experience)
Interprets the reasons for statistical errors, misinterpretations, and false positives.
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Level 3 Behaviors
(Moderate Experience)
Works with teams in using different kinds of cross-validation to test results of predictive models.
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Level 4 Behaviors
(Extensive Experience)
Researches and lists the cases that are predicted wrongly and then learns how to improve.
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Level 5 Behaviors
(Mastery)
Stays current with the latest research on predictive analytics.
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3 Data Scientist I - Skill and Competency
Proficiency Level - 3
4 Skill and Competency - Data Scientist I
Proficiency Level - 4
5 Competency for - Data Scientist I
Proficiency Level - 5

Summary of Data Scientist I skills and competencies

There are 0 hard skills for Data Scientist I.
18 general skills for Data Scientist I, Big Data Analytics, Business Intelligence, Data Analytics, etc.
6 soft skills for Data Scientist I, Business Acumen, Predictive Analytics, Critical Thinking, 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 Scientist I, he or she needs to be proficient in Business Acumen, be proficient in Predictive Analytics, and be proficient in Critical Thinking.

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