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Occupational Profile
Emerging Occupations

Data Miner

This is an emerging occupation. It may have evolved from an existing occupation or emerged in response to consumer needs or technological advances. In general, data miners explore large amounts of data to identify patterns and relationships between variables and make predictions (for example, predict what groups of people will do in the future based on how they have acted in the past).

  • Avg. Salary N/A
  • Avg. Wage N/A
  • Minimum Education 4 years post-secondary
  • Outlook N/A
  • Employed 2,700
  • In Demand Lower
Also Known As

Data Mining Analyst, Data Processing Specialist, Data Scientist

Skills Shortage

Employers that Recruited in the Last 2 Years

48%
48%
Average Wage
Starting
Overall
Top
  • Certification Not Regulated
  • Strength Required Lift up to 5 kg
NOC & Interest Codes
The Data Miner is part of the following larger National Occupational Classification (NOC).
Database Administrators
NOC code: 2172.2
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

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 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 More

Duties
Updated Dec 19, 2016

Data mining combines statistics, artificial intelligence (AI) and database research. Data miners focus on identifying predictors of relevant or predetermined outcomes.

There are three stages in data mining:

  • initial exploration (for example, generate a summary and description of the key variables and values)
  • model building or pattern identification
  • model testing (for example, applying the model to new data to generate predictions).

In general data miners:

  • clean the data (remove data that may have errors or contradict other data in the pattern)
  • select relevant subsets of records to reduce the amount of data to explore
  • identify the most relevant variables
  • determine the complexity and nature of models required
  • use techniques such as bagging (averaging), stacking, bootstrapping and meta-learning
  • apply different models (for example, association mining, classification mining, clustering mining, neural networks, Bayesian networks) to the same data and compare 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 miners 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 Dec 19, 2016

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

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

  • Strength Required Lift up to 5 kg
Skills & Abilities
Updated Dec 19, 2016

Data miners need the following characteristics:

  • an aptitude for and interest in mathematics, statistics 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 backgrounds
  • strong attention to detail.

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

Educational Requirements
Updated Dec 19, 2016

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

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

The minimum academic requirement is a bachelor's degree in computing science, statistics or computer engineering, but 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.

Grande Prairie Regional College

For a broad list of programs and courses that may be related to this occupation try searching using keywords.

Employment & Advancement
Updated Dec 19, 2016

Emerging occupations typically are the result of:

  • an increased human need (for example, alternate sources of energy)
  • 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 data miners is unknown.

Data miners 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 jobs are located in major urban areas.

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

The employment outlook in this occupation will be influenced by a wide variety of factors including:

  • trends and events affecting overall employment (especially in the industries listed above)
  • location in Alberta
  • employment turnover (work opportunities generated by people leaving existing positions)
  • occupational growth (work opportunities resulting from the creation of new positions that never existed before)
  • size of the occupation.
Wage & Salary
Updated Dec 19, 2016

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

Salary data is available  for the larger National Occupational Classification 2172: Database analysts and data administrators as part of the 2015 Alberta Wage and Salary Survey.

Database analysts and data administrators
NOC code: 2172

Survey Methodology

Survey Analysis

Overall Wage Details
Average Wage
Average Salary
Hours Per Week

Hourly Wage
For full-time and part-time employees
  • Low
  • High
  • Average
  • Median
Starting
Overall
Top
Wages* Low (5th percentile) High (95th percentile) Average Median
Starting $16.06 $49.50 $34.63 $34.62
Overall $21.65 $59.23 $43.51 $44.00
Top $27.75 $84.13 $53.60 $52.49

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.

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.


Industry Information
Oil & Gas Extraction
Professional, Scientific & Technical Services
ALBERTA, ALL INDUSTRIES
Public Administration
Business, Building and Other Support Services (aka Management, Administrative, and other Services)

Skills Shortage

Employers that Recruited in the Last 2 Years

48%
48%

Recruiting Employers that Experienced Hiring Difficulties

18%
18%

Employers with Unfilled Vacancies of over 4 Months

9%
9%

2015 Vacancy Rate

3%
Related High School Subjects
  • English Language Arts
  • Mathematics
  • Science
    • Physics
Related Post-Secondary Field of Study
  • Business, Management and Administrative Studies
  • Computer and Information Technology
  • Health Care and Medical Sciences
  • Mathematics
  • Sciences
  • Social Sciences, Law and Religious Studies

Updated Mar 09, 2016. 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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