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Updated / Emerging Occupations

Data Scientist

Data scientists explore large amounts of data to identify patterns and relationships between variables. They use these patterns to make predictions. For example, they might look at a group of people who share certain traits and predict what they will do in the future based on what they have done in the past.

This is an emerging occupation. It may have evolved from an existing occupation or emerged in response to consumer needs or technological advances.

Also Known As

Data Miner, Data Mining Analyst, Data Processing Specialist

NOC Codes

In Canada, the federal government groups and organizes occupations based on a National Occupational Classification (NOC) system. This alis occupation may not reflect the entire NOC group it is part of. Data for the NOC group can apply across multiple occupations.

The NOC system is updated every 5 years to reflect changes in the labour market. Government forms and labour market data may group and refer to an occupation differently, depending on the system used.

This occupation has not yet received an official NOC code. However, it is considered similar to the following historical NOC codes. CAUTION—As this occupation is only similar to these NOC codes, related details and labour market information may not be accurate:

  • 2006 NOC: Database Administrators (2172.2) 
  • 2006 NOC-S: Database Analysts and Data Administrators (C072) 
  • 2011 NOC: Database analysts and data administrators (2172) 
  • 2016 NOC: Database analysts and data administrators (2172) 
Interests & Abilities

In Alberta, this occupation is part of 1 or more 2006 National Occupational Classification (NOC) groups. If there are multiple related NOC groups, select a NOC heading to learn about each one.

Database Administrators*

2006 NOC: 2172.2

*This data is for a NOC group that is similar to the Data Scientist occupation.

Interest Codes

Interest Codes for This NOC Group
INNOVATIVE

Interest in co-ordinating information to develop policies and procedures for network access and usage and for the backup and recovery of data

METHODICAL

Interest in precision working to implement and monitor data administration solutions, standards and procedures

DIRECTIVE

Interest in consulting to conduct research and to advise on the collection, availability and suitability of data; may lead and co-ordinate teams of data administrators in the development and implementation of data policies, standards and models

Your Interest Codes

To identify or change your interest codes, complete the Interests Exercise in CAREERinsite.

Reading Interest Codes
A Quick Guide

The interest code helps you figure out if you’d like to work in a particular occupation. 

It’s based on the Canadian Work Preference Inventory (CWPI), which measures 5 occupational interests: Directive, Innovative, Methodical, Objective, and Social.

Each set of 3 interest codes for this NOC group is listed in order of importance.

A code in capital letters means it’s a strong fit for the occupation.

A code in all lowercase letters means the fit is weaker.

Learn About Interests

Abilities

Typical ability expectations for this NOC group
Your abilities

To fill in or change the values for your abilities, complete the Abilities Exercise in CAREERinsite.

Mental Abilities

General Learning Ability

Verbal Ability

Numerical Ability

Visual Abilities

Spatial Perception

Form Perception

Clerical Perception

Physical Abilities

Motor Coordination

Finger Dexterity

Manual Dexterity

Understanding Abilities

A Quick Guide

You are born with abilities that help you process certain types of information and turn it into action. These abilities influence which skills you can learn more easily.

The abilities or aptitudes shown for this NOC group come from the General Aptitude Test Battery (GATB). The GATB measures 9 aptitudes. It groups them into 3 categories: mental, visual, and physical.

The abilities scores range from 1 to 5, with 5 being stronger.

Learn About Abilities

Duties
Updated Mar 31, 2022

Data science combines statistics, artificial intelligence (AI), database research, and software development. Data scientists identify past actions that predict relevant future outcomes.

Data science includes at least 4 stages:

  • Initial exploration (for example, analyze data to understand the quality and structures). Generate a summary and description of the key variables and values based on initial exploration
  • Data model building or value-based pattern identification
  • Model testing (for example, applying the model to new data to generate predictions)
  • Model deployment (using the model to make predictions and/or decision in the real world)

In general, data scientists clean the data, which involves removing data that may have errors or contradict other data in the pattern. They also:

  • Select relevant subsets of data records to reduce the amount of information to explore
  • Identify the most relevant data variables
  • Determine the complexity and nature of data, information or business models required
  • Use techniques such as bagging (averaging), stacking, bootstrapping and meta-learning
  • Apply different models (for example, association mining, classification mining, cluster mining, neural networks, Bayesian networks or support vector machines) to the same data
  • Compare model results to select a preferred model
  • Apply the selected model to new data to find patterns and clusters or test and generate predictions or estimates of expected outcomes

Some data scientists may use prescriptive analytics (building different prediction models based on various potential decision actions) to guide decision makers to a desired outcome.

Working Conditions
Updated Mar 31, 2022
  • Strength Required Lift up to 5 kg

Data scientists work in offices with sophisticated information technology. They work standard weekday office hours but may also be required to work overtime to meet project deadlines.

Data scientists often work on several different projects at the same time. They generally work in a team environment but may work alone.

Traits & Skills
Updated Mar 31, 2022

Data scientists need:

  • An aptitude for and interest in statistics, artificial intelligence, and databases
  • An interest in applying scientific principles to solve practical problems
  • The ability to analyze information and understand abstract relationships
  • The ability to think logically, organize projects, and carry them out
  • The ability to work alone as well as with others
  • The ability to communicate with individuals from different technical and cultural backgrounds
  • Attention to detail

Data scientists should enjoy synthesizing data, applying statistical theories and methods, and working with others to understand and solve problems.

In Alberta, this occupation is part of 1 or more 2011 National Occupational Classification (NOC) groups. If there are multiple related NOC groups, select a NOC heading to learn about each one.

Top 10 Skills Employers Are Looking For

Database analysts and data administrators*

2011 NOC: 2172

*This data is for a NOC group that is similar to the Data Scientist occupation.

This chart shows which job skills are currently in highest demand for this occupational group. It was created using this occupation's 85 most recent Alberta job postings, collected between Oct 27, 2021 and Sep 26, 2022.

Review these skills to learn:

  • Whether or not this occupation matches your skill set
  • What training you may need to get these skills
  • What skills to highlight in your resumé, cover letter, and interview.
Tasks: Design, construct, modify, implement and test data models and database management systems
Computer and Technology Knowledge: MS Office
Tasks: Operate database management systems to analyze data
Computer and Technology Knowledge: MS Windows
Tasks: Design and develop database
Tasks: Research and document data requirements, data collection and administration policy, and data access rules
Computer and Technology Knowledge: Database software
Construction Specialization: Organized
Design, construct, modify, implement and test data models and database management systems
Operate database management systems to analyze data
Educational Requirements
Updated Mar 31, 2022
  • Minimum Education 4 years post-secondary

Most emerging occupations develop from more than one occupation. People working in this occupation may come from a variety of education and training backgrounds. Before enrolling in an education program, prospective students should contact associations and employers in this field to investigate education options and employment possibilities.

Data scientist is not an entry-level position. Employers generally prefer applicants who have several years of related experience.

The minimum academic requirement is a bachelor’s degree in data science, data analytics, computing science, statistics, computer engineering, or another highly quantitative field. A graduate degree (master’s or doctoral) usually is required for higher-level positions. A doctoral degree (PhD) is required to conduct independent research.


Related Education

The following schools offer programs or courses that are related to this occupation but are not required to enter the field.

Bow Valley College
Grant MacEwan University

To expand or narrow your search for programs related to this occupation, visit Post-Secondary Programs.

Completing a program does not guarantee entrance into an occupation. Before enrolling in an education program, prospective students should look into various sources for education options and employment possibilities. For example, contact associations and employers in this field.

Certification Requirements
Updated Mar 31, 2022
  • Certification Not Regulated

There is currently no provincial legislation regulating this occupation in Alberta.

Employment & Advancement
Updated Mar 31, 2022

Emerging occupations typically are the result of:

  • An increased human need
  • Technological advances
  • Greater specialization within an occupation

Often there are too few people working in an emerging occupation to gather survey information. Therefore, it can be difficult to define advancement opportunities or employment outlook. Some Albertans already are working in this emerging occupation, but future demand for it is unknown.

Data scientists work for a variety of employers including:

  • Medical and educational research agencies
  • Natural resource companies
  • Environmental research companies
  • Market research companies
  • Pharmaceutical companies
  • Large retail companies
  • Post-secondary schools

Most data scientists find employment in major urban areas. However, remote work from home or a different worksite is becoming more common.

Outstanding individuals who have graduate degrees and many years of experience may move into management positions or become private consultants.

Industry Concentration

This section shows the industries where the majority of people in this occupation work. The data is based on the 2016 Census.

In Alberta, this occupation is part of 1 or more 2016 National Occupational Classification (NOC) groups.

In the 2172: Database analysts and data administrators* occupational group, 78.5% of people work in:

*This data is for a NOC group that is similar to the Data Scientist occupation.

Employment Outlook

Employment outlook is influenced by a wide variety of factors including:

  • Time of year (for seasonal jobs)
  • Location in Alberta
  • Employment turnover (when people leave existing positions)
  • Occupational growth (when new positions are created)
  • Size of the occupation
  • Trends and events that affect overall employment

Explore emerging workplace trends in Alberta that could affect this occupation.

In Alberta, the 2172: Database analysts and data administrators* occupational group is expected to have an above-average annual growth of 2% from 2019 to 2023. In addition to job openings created by employment turnover, 77 new positions are forecasted to be created within this occupational group each year.

*This data is for a NOC group that is similar to the Data Scientist occupation.

Note
NOC groups often include several related occupations. Although there is labour market data for the larger NOC group, this occupation makes up only a part of that group. It means data for this occupation may be different than the data shown. For example, only some of the new positions to be created will be for this occupation. It also applies to other data for the NOC group such as number of people employed.

Source: Alberta Regional Occupational Demand Outlook

Related Alberta Job Postings
Wage & Salary
Updated Mar 31, 2022

Often there are too few people working in an emerging occupation to gather survey information. Therefore, no current provincial salary data is available for this occupation.

In Alberta, this occupation is part of 1 or more 2016 National Occupational Classification (NOC) groups. If there are multiple related NOC groups, select a NOC heading to learn about each one.

Database analysts and data administrators*

2016 NOC: 2172

*This data is for a NOC group that is similar to the Data Scientist occupation.

Average Wage
$45.34
Per Hour
Average Salary
$89,162.00
Per Year
Average Hours
37.6
Per Week
Average Months on Payroll
12
Survey Methodology Survey Analysis

Source
2021 Alberta Wage and Salary Survey

NOC 2172 Wage Profile

Unless otherwise noted, the data shown here is for all industries and all regions in Alberta.

All wage estimates are hourly except where otherwise indicated. Wages and salaries do not include overtime hours, tips, benefits, profit shares, bonuses (unrelated to production), and other forms of compensation.

To see the full survey data for this NOC group, visit the wage profile.

Other wage sources
To make an informed wage and salary decision, research other wage sources [pdf] to supplement this data.

A: High Reliability
Data Reliability Code Definition

High Reliability, represents a CV of less than or equal to 6.00% and 30 survey observations and/or represents 50% or more of all estimated employment for the occupation.


Hourly Wage

For full-time and part-time employees
  • Low
  • High
  • Average
  • Median
Starting
Overall
Top

Hourly Wage

For full-time and part-time employees
Wages* Low (5th percentile) High (95th percentile) Average Median
Starting $21.60 $55.96 $36.78 $36.06
Overall $25.76 $69.68 $45.34 $45.19
Top $29.28 $82.15 $53.76 $53.33

Swipe left and right to view all data. Scroll left and right to view all data.

* All wage estimates are hourly except where otherwise indicated. Wages and salaries do not include overtime hours, tips, benefits, profit shares, bonuses (unrelated to production) and other forms of compensation.

Pay brackets for hourly wages

  • Starting pay: average pay offered for entry-level positions
  • Overall pay: average pay across all employees in this occupation
  • Top pay: average pay offered to top-paid employees

Industry Information

Public Administration
Professional, Scientific & Technical Services
ALL INDUSTRIES
Manufacturing
Health Care & Social Assistance
Finance, Insurance, Real Estate, Leasing
Information, Culture, Recreation

Skills Shortage

Employers that Recruited in the Last 2 Years
19%
19%)
Recruiting Employers that Experienced Hiring Difficulties
20%
20%
Employers with Unfilled Vacancies of over 4 Months
0%
0%
Vacancy Rate
N/A
Related Post-Secondary Field of Study
  • Business, Management and Administrative Studies
  • Computer and Information Technology
  • Engineering, Architecture and Related Studies
  • Health Care and Medical Sciences
  • Mathematics
  • Sciences
  • Social Sciences, Law and Religious Studies

Updated Mar 31, 2022. The information contained in this profile is current as of the dates shown. Salary, employment outlook, and educational program information may change without notice. It is advised that you confirm this information before making any career decisions.

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