Job description Data Analytics Consultant in the Banff–Jasper–Rocky Mountain House Region

Find out what work is like for a data analytics consultant in Canada. This work description is applicable to all Database analysts and data administrators (NOC 21211).

Data scientists

Description

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. They are employed by consulting firms, universities, banks and information technology departments in the private and public sectors.

Work week duration

Data scientists usually work between 35 to 40 hours per week.
Between 35 to 40 hours

Job duties

Here are some of the main activities and tasks that Data scientists have to perform, and some of the physical demands they involve:

  • 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

Physical demands Help - Physical Demands

  • Sitting
  • Handling material manually
  • Making repetitive motions

Physical demands

Physical demands are the physical activities that the job requires the worker to do. Physical demands are selected according to the likeliness that workers will have to perform them for at least half of the time they spend at work.

Workplaces and employers

Here are the typical workplaces where Data scientists are employed and some of their main characteristics:

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

Work environment Help - Physical Work Environment

  • Indoors, environmentally controlled

Physical proximity from others Help - Physical proximity from others

  • Somewhat close (e.g. share office)

Work environment

The work environment refers to the physical setting in which people work. The characteristics and conditions of the work environment are selected according to the likeliness that workers will be exposed to them at least once a week.

Physical proximity from others

Physical proximity from others refers to the physical distance between individuals in the workplace. The likeliness that the job requires to perform tasks while being physically close to other people is rated on a scale with 3 levels: "Somewhat close", "Close" and "Very close".

Related job titles

Here are some other related job titles that are found in the same occupational category (NOC 21211), and a list of similar occupations:

  • data architect
  • data scientist
  • machine learning engineer
  • machine learning specialist
  • quantitative analyst

Similar occupations Help - Similar occupations

Similar occupations

This section lists other occupations that are part of the same broad occupational category as Data scientists in the National Occupational Classification (NOC). These occupations involve similar core qualifications but involve different responsibilities. To see more similar occupations, use the Job Transition Tool.

Sources Occupational and Skills Information System & National Occupational Classification

Labour Market Information Survey
Date modified: