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Data scientists

OaSIS code 21211.00

Data scientists use advanced analytics technologies, including machine learning and predictive modelling, to support the identification of trends, scrape information from unstructured data sources and provide automated recommendations.

Overview

Also known as

  • Data architect
  • Data scientist
  • Machine learning engineer
  • Machine learning specialist
  • Quantitative analyst

Main duties

This group performs some or all of the following duties:

  • Implement cutting-edge techniques and tools in machine learning, deep learning and artificial intelligence to make data analysis more efficient
  • Perform large-scale experimentation to identify hidden relationships between variables in large datasets
  • Create advanced machine learning algorithms such as regression, simulation, scenario analysis, modeling, clustering, decision trees and , neural networks
  • Prepare and extract data using programming language
  • Implement new statistical, machine learning, or other mathematical methodologies to solve specific business problems
  • Visualize data in a way that allows a business to quickly draw conclusions and make decisions
  • Develop artificial intelligence models and algorithms and implement them to meet the needs of the organization.
  • Coordinate research and analysis activities using unstructured and structured data and use programming to clean and organize data

Additional information

No data has been provided for this section.

Similar occupations classified elsewhere

Exclusions:

  • Computer and information systems managers (20012)
  • Mathematicians, statisticians and actuaries (21210)
  • Information systems specialists (21222)
  • Database analysts and data administrators (21223)
  • Software engineers and designers (21231)
  • Computer engineers (except software engineers and designers) (21311)

NOC hierarchy breakdown

NOC version

NOC 2021 Version 1.0

Broad occupational category

2 – Natural and applied sciences and related occupations

TEER

1 – Occupations usually require a university degree

Major group

21 – Professional occupations in natural and applied sciences

Sub-major group

212 – Professional occupations in applied sciences (except engineering)

Minor group

2121 – Mathematicians, statisticians, actuaries and data scientists

Unit group

21211 – Data scientists

Occupational profile

21211.00 – Data scientists

Work characteristics

Work characteristics gathers the various components describing the work environment of each occupation, such as employers, work activities, and the work context. Each category displays up to 10 descriptors in descending order based, firstly, on their attributed ratings by the level of complexity (for Work Activities) or other measurement dimensions (for Work Context), and secondly, in alphabetical order. The whole list of descriptors and their ratings can be expanded at the bottom of each page.

Work Activities

Proficiency or complexity level
Analyzing Data or Information
5 - Highest Level
Interacting with Computers
5 - Highest Level
Interpreting the Meaning of Information for Others
5 - Highest Level
Processing Information
5 - Highest Level
Providing Consultation and Advice
5 - Highest Level

Work Context

Structural Job Characteristics

Structured versus Unstructured Work
Degree of freedom to determine tasks and priorities
3 - Moderate amount of freedom
Work Week Duration
Worked hours in a typical week
2 - Between 35 to 40 hours

Physical Work Environment

Physical Proximity
Physical distance from others
3 - Somewhat close (e.g. share office)

Physical Demands

Sitting
Duration
5 - All the time, or almost all the time
Standing
Duration
1 - Very little time
Bending or Twisting the Body
Duration
1 - Very little time

Interpersonal Relations

Contact with Others
Frequency
4 - Every day, a few times per day
Duration
3 - About half the time
Work with Work Group or Team
Importance
3 - Important
Frequency
3 - Once a week or more but not every day

Workplaces/employers

  • Banks
  • Consulting businesses
  • Information technology departments in the private and public sectors
  • Universities

Skills and abilities

This section displays the various competencies required for an occupation. Each category displays up to 10 descriptors in descending order based, firstly, on their attributed ratings by the level of proficiency (for Skills and Abilities) or importance (for Personal Attributes) and secondly, in alphabetical order. The whole list of descriptors and their ratings can be expanded at the bottom of each page.

Abilities

Proficiency or complexity level
Categorization Flexibility
4 - High Level
Deductive Reasoning
4 - High Level
Fluency of Ideas
4 - High Level
Inductive Reasoning
4 - High Level
Information Ordering
4 - High Level

Skills

Proficiency or complexity level
Digital Literacy
5 - Highest Level
Numeracy
5 - Highest Level
Systems Analysis
5 - Highest Level
Critical Thinking
4 - High Level
Decision Making
4 - High Level

Personal Attributes

Importance
Analytical Thinking
5 - Extremely important
Attention to Detail
5 - Extremely important
Innovativeness
5 - Extremely important
Active Learning
4 - Highly important
Adaptability
4 - Highly important