Data scientists
High opportunity occupation
Career Overview
Data scientists analyze data to solve real-world problems. They draw from their fields of math, stats, artificial intelligence and computer science to gain insights, identify patterns and help organizations make good decisions.
Job Titles
Duties
Data scientists:
- Use data to model problems and find solutions
- Collect and organize data using statistical methods
- Extract, clean and sort data using programming languages
- Analyze data using artificial intelligence technologies, including machine learning and predictive modelling
- Find relationships within datasets
- Develop algorithms to analyze data, find patterns and make predictions
- Examine and interpret their findings
- Present their findings to organizations to help them make better decisions and improve their business practices and systems
Earnings
Earnings is income that workers receive in exchange for their labour. Depending on the type of employment, earnings can be in the form of wages (hourly), salaries (fixed monthly or annual) or self-employed earnings.
Work Environment
# Workers Employed
1,825% Employed Full Time
70%Data scientists work in the private and public sectors. They work for consulting firms, universities, banks and governments. They also work in information technology (IT) and other departments in different organizations.
Some work in offices. Many work remotely or from home.
The work of the data scientist is analytical and precise. It also requires creativity and the determination to find connections and solve problems.
Data scientists spend most of their time sitting at their computers. They must take care to avoid straining their eyes, back, neck, shoulders and other joints.
Career Pathways
Data scientists usually start in junior analyst roles. With experience, they may take on more responsibility and leadership. Some move into senior roles such as director of data science or chief information officer (CIO).
Some data scientists choose to focus on the data/technical side. Others take a more business-focused path in which they manage projects and work with business teams.
Occupational Interests
It’s important to understand what kinds of occupations align with your interests.
For more about occupational interests visit Skills for the Future Workforce > Characteristics.
Here are the top occupational interest(s) for this career profile:
Education, Training and Skills
- A bachelor's degree in statistics, mathematics, computer science, software engineering, computer systems engineering or a related discipline or completion of a college program in computer science is usually required
- A master's or doctoral degree with a focus on machine learning, data science or a related field
- Experience in programming, statistical modelling and machine learning
Data scientists need strong analytical, math and problem-solving skills, and they must be detail-oriented. They also need good communication skills so they can share their findings with people who may not have a technical background.
Because new technologies for analyzing data are always emerging, ongoing education is essential.
Education programs in B.C.
Top Skills
Every job calls for a certain set of skills. Knowing those skills is the first step in finding a good career fit.
Here, you will find the 10 most relevant workplace skills. Some are more important to achieving success in a certain career than others. These skills may come naturally to you or you may need to gain them through education, training and experience.
See the list of work-related skills below, ranked in order of importance for this career. Check out the list and see if this career matches your skills—take that first step!
Understanding written sentences and paragraphs in work-related documents.
Using logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions or approaches to problems.
Giving full attention to what other people are saying, taking time to understand the points being made, asking questions as appropriate, and not interrupting at inappropriate times.
Talking to others to share information effectively.
Being able to solve novel, ill-defined problems in complex, real-world settings.
Considering the relative costs and benefits of potential actions to choose the most appropriate one.
Communicating effectively in writing as appropriate for the needs of the audience.
Understanding how new information could be used to solve current and future problems in making decisions.
Determining how a system should work and how changes in conditions, operations and the environment will affect outcomes.
Identifying measures or indicators of system performance and the actions needed to improve or correct performance, while meeting the goals of the system.
Labour Market Statistics
Discover data, facts and information that have been gathered and analyzed. Learn about the characteristics of the economy and labour market in B.C.
Employment
Find out about employment types and trends by region and industry.
Employment
1,825Employment by Region
| Region | Employment | % Employment of this Occupation |
|---|---|---|
| Cariboo | 0 | 0.0% |
| Kootenay | 0 | 0.0% |
| Mainland/Southwest | 1,615 | 88.5% |
| North Coast and Nechako | 0 | 0.0% |
| Northeast | 0 | 0.0% |
| Thompson-Okanagan | 50 | 2.7% |
| Vancouver Island/Coast | 155 | 8.5% |
Labour Market Outlook
The B.C. Labour Market Outlook is a 10-year forecast of the expected supply and demand for labour in the province. It’s usually updated every year. The purpose is to provide British Columbians with the knowledge to make informed decisions on careers, skills training, education and hiring.
Forecasted Job Openings (2024-2034)
840Forecasted Job Openings
Forecasted Employment Growth Rate
Composition of Job Openings
Job Openings by Region (2024-2034)
| Region | Job Openings | Avg. Annual Employment Growth |
|---|---|---|
| Cariboo | Not available | Not available |
| Kootenay | Not available | Not available |
| Mainland/Southwest | 760 | 2.5% |
| North Coast and Nechako | Not available | Not available |
| Northeast | Not available | Not available |
| Thompson-Okanagan | 20 | 3.4% |
| Vancouver Island/Coast | 60 | 1.5% |
Industry Highlights
Learn about the opportunities in B.C.'s major industries, including employment trends, earning potential, locations of work and more.
Forecasted Job Openings by Industry
| Industry | Job Openings (2024-2034) |
|---|---|
| Professional, Scientific and Technical Services | 570 |
| Finance, Insurance and Real Estate | 80 |
| Information, Culture and Recreation | 50 |
| Retail Trade | 30 |
| Public Administration | 20 |
Insights from Industry
Data science is a new and expanding field, and demand for workers is high. Data scientists who specialize in specific areas, like finance, health care or marketing, may be in especially high demand.
Ethics are key to this role. Data scientists must understand the importance of protecting privacy, avoiding bias and ensuring the responsible use of data.
Resources
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BC Statswww2.gov.bc.ca/gov/content/data/about-data-management/bc-stats
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BC Tech Associationwww.wearebctech.com
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Canada's Association of I.T. Professionalswww.cips.ca
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Canada's Association of Information Technology (IT) Professionals - British Columbiawww.bc.cips.ca
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The Canadian Advanced Technology Allianceinnovationsoftheworld.com/canadian-advanced-technology
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Data Management Association (DAMA)www.dama.org/cpages/home
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First Nations Technology Councilwww.technologycouncil.ca
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Information and Communications Technology Councilwww.ictc-ctic.ca
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Information Resource Management Association of Canadawww.irmac.ca
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Information Systems Audit and Control Associationwww.isaca.org
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International Institute of Business Analysiswww.iiba.org
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International Institute of Business Analysis – Career Centrewww.iiba.org/Careers/IIBA-Career-Centre-Find-business-analyst-jobs.aspx
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Statistics Canadawww.statcan.gc.ca/en/start
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Technation.ca formerly the Information Technology Association of Canadaitac.ca
Career Videos
Watch the video below to see a day in the life of a machine learning engineer.
Watch the video below to see a day in the life of a machine learning engineer.
