Introduction
Canada’s service sector employs more than three-quarters of the country’s workforce. It’s crucial to have a thriving industry in everything from transportation to chemicals to lumber and paper products. The government has abundant natural resources, including gold, nickel, aluminum, and crude oil.
The IT industry (Data Science and AI) is expected to grow 5.3 percent in 2022 and 22.4 percent from 2021 to 2024. More than three times as many tech firms that have conducted acquisitions in the last decade experienced revenue growth of at least 5% in the prior year as their counterparts.
Canada’s technology industry is seeing unprecedented growth at the moment. Technological sectors such as artificial intelligence and clean technology are propelling the cities of Toronto, Montreal, and Vancouver to prominence. Canada has made an all-out endeavour to attract technological talent. In industries such as banking, healthcare, finance, insurance, media and entertainment, telecom and e-commerce, there is a raising need for highly skilled Data Scientists and AI specialists. Professionals are in high demand, but there is now a shortage.
What is Data Science?
Data science is a discipline that combines domain expertise, computing abilities, and math and statistics understanding to derive actionable insights from large amounts of data. To construct artificial intelligence (AI) systems that can perform tasks that ordinarily require human intelligence, machine learning algorithms are applied to various data types, including numbers, text, images, video, and audio. Analysts and other business users can leverage the insights generated by these systems to create commercial value.
What makes a job in data science so appealing?
Several industries are attempting to profit from their data, including finance, retail, information technology, and banking. All of them are searching for data scientists. As a result, Canada’s data science industry is booming. In light of IBM’s claim that the twenty-first century’s most sought-after employment is that of a business owner, it is a gratifying career choice for many. Anyone from any background can become a Data Scientist in this industry.
Some of the most popular data science positions are data scientist, data analyst, data engineer, machine learning engineer, research scientist, business intelligence developer, data architect, statistician, and prominent data engineer.
How much does a Canadian data scientist make?
A growing number of corporations are realizing the value of leveraging analytical data to better their business processes. Professionals in the field of data science are paid no less!
The average annual compensation for a data scientist in Canada, according to payscale.com, is CA$79981. A data scientist in Canada can expect to earn a yearly income of CA$80,646, according to Indeed.com’s pay data. According to Glassdoor.com, the average compensation for a data scientist in Canada is CA$87,248 per year. The annual wage for a data scientist in Canada at CA$129,596 to SalaryExpert.com. For a data scientist with less than three years of experience, the average salary is CA$91,102 a year. However, the average salary for a senior data scientist (8+ years of experience) is $160,846.
Job seekers who want to pursue a career in data science can do so in Ottawa, Canada’s capital. In Ottawa, the average annual compensation for a data scientist is CA$96,766 (Glassdoor.com). Indeed reported a yearly wage of $84070 for an Ottawa-based data scientist. A data scientist in Ottawa can expect an annual salary of C$76178. (Payscale)
Do you want to go into the field of data science as a career?
Managers’ Data Science Management at all levels of an organization might benefit from taking a data science course to improve their managerial skills and operations.
A growing emphasis on explainable AI, which provides information to help people understand how AI and machine learning models work and how much they can trust their findings in making decisions, and a linked focus on liable AI principles, which ensures that AI technologies are fair, impartial, and transparent are some of the future trends that will have an impact on data scientists’ work.
Due to the complexity of enormous data management and AI training and capabilities required to construct AI, many companies are looking for AI talent.
Prominent data engineers, AI engineers, business intelligence developers, ML engineers, data scientists, research scientists, and robotics scientists are some of the most sought-after AI jobs in the industry.
In Canada, how much do artificial intelligence (AI) employees make?
Artificial intelligence is already attracting a sizable chunk of the current IT talent pool, who see it as a source of high income and a rewarding career path. In Canada, a person with expertise in Artificial Intelligence is paid an average salary of CA$99,000 per year, according to payscale.com’s data. Annual compensation for a data scientist in Canada is CA$79,000, according to Talent.com. According to Glassdoor.com, the annual compensation for a data scientist in Canada is CA$102,973. According to an economic research institution, an average salary of $123,363 per year for a data scientist in Canada. There has been a steady rise in the importance of artificial intelligence (AI) in Ottawa’s economy during the past few years. In Ottawa, AI Engineers earn an annual salary of $81,838.
Are you interested in a career in artificial intelligence?
The artificial intelligence (AI) area has created a wide range of opportunities for prospective professionals worldwide. The wisest decision you can make is to take DataMites’ Artificial Intelligence Certification Training. DataMites is a global training centre for data science and AI. Only those who have worked in the field for many years may thoroughly understand AI. Professionals in the data science and artificial intelligence field can benefit from this DataMites AI Engineer Certification Training course.
Data Science Expertise That’s in High Demand
Mathematics and Statistics
Mathematical and statistical skills are a prerequisite for data scientists. Efficiencies are required in both of these areas. When a company relies on data, it hires data scientists to conduct research and development on various statistical approaches. The results are vital for making essential business decisions. To become an expert in machine learning, data scientists must have a good knowledge of calculus and mathematics. No one should be surprised by the fact that statistics are required.
Programming
Programming is an essential part of Data Science. To succeed in the role of a data scientist, one must have a working knowledge of many computer languages. The best-paid workers in Canada are those with a background in computer programming. A handful of the programming languages that one should know to include Java, Python, Hadoop, SQL, and C++.
Data Communication and Visualization
A crucial part of data analysis is communicating and visualizing the results. It’s challenging to operate with unstructured data. Data must be presented and organized clearly and easily to understand. It’s critical because many corporate marketing decisions are based only on statistics. It all relies on how the data is interpreted. Data scientists can use various tools, including Tableau and Power BI, to improve their data communication skills.
Software Engineering
Massive amounts of data necessitate the use of software engineering skills and competencies. Employers are willing to pay more for data scientists with software engineering abilities.
Data Analytics and Remodeling
Data scientists are responsible for the quality of the insights they produce. The data scientist’s ability to model and analyze data is expected to be excellent. Modelling data will necessitate effective communication, in-depth research, and the application of critical thinking. Data scientists must conduct tests, analyze data, and build various models to understand and anticipate the outcomes of their experiments.
Communication
Data has no value unless it can be shared. Candidates for the post of data scientist should have excellent verbal and written communication abilities. As essential as outlining the route from A to B or discussing data visualization methods and giving corporate growth estimates and marketing statistics, it might be as simple as that.
Extraction, Loading, and Transformation of Data
Many databases, including MySQL, Google Analytics, and MongoDB, are tapped for data. The greater the number of sources, the better the data. An appropriate structure or format is used to evaluate this unstructured material. After analyzing the data, it must be stored in a data warehouse. Experts in this field analyze this section’s data. Data science applicants with experience in extracting, manipulating, and importing data will have a bright career ahead of them.
Intellectual Thinking
Data scientists must be able to look beyond the box and discern the true significance of the data they collect. They should be able to think through problems and come up with creative solutions. A data scientist must be curious to study and analyze data in various ways.
Machine Learning and Deep Learning
Machine learning is known as making computers and gadgets smart enough to make their own decisions and think for themselves. To minimize financial losses, algorithms and the ability to make profit projections are essential for data scientists. The term “deep learning” refers to using neural networks to learn. In the field of machine learning, Python is the most important language to use. Deep learning models can be built using TensorFlow, a well-known Python package.
Canada’s Best Data Science Career Opportunities
| Job Title | Job Description | Average Annual Salary |
| Senior Data Scientist | After earning a master’s degree in data science, one of the most sought-after occupations is that of senior data scientist. | CAD 120,000 (Rs 70 lakh) |
| Business Intelligence Analyst | BI analysts use data to help businesses make wise decisions. Top organisations use them to programme tools and create data models for visualisation. | CAD 77638 (Rs 45 lakh) |
| Data Architect | Design, development, deployment, and administration of an organization’s data architecture are all responsibilities of a Data Architect. | CAD 81,000 (Rs 47 lakh) |
| Business Intelligence Developer | A BI developer is a software engineer that specialises in analysing and visualising data using business intelligence (BI) tools. Data scientists and software engineers are ideal candidates for this position. | CAD 81,945 (Rs 48 lakh) |
| Application Architect | The behaviour of apps in a business is described by the applications architecture, which focuses on the interactions between applications and users. Among the gaming and IT industries, it’s a sought-after commodity. | CAD 110,000 (Rs 64 lakh) |
| Big Data Engineer | In terms of employment opportunities, Big Data Engineers come out on top, followed by Data Science. The job of a data engineer is to look for patterns in large datasets and create algorithms that turn unstructured data into meaningful information. | CAD 120,000 (Rs 70 lakh) |
| Business Analyst | As a business analyst, you’ll need to be able to communicate effectively, have a working grasp of programming, and be able to make quick business choices. | CAD 78,574 (Rs 46 lakh) |
| Data Scientist | It is the job of Data Scientists to sift through mountains of data and extract meaningful insights from it for data-driven enterprises. | CAD 107,500 (Rs 63 lakh) |
| Machine learning scientist | When it comes to making smart decisions, machines rely on the expertise of machine learning specialists. | CAD 162,625 (Rs 95 lakh) |
| Data Analyst | After completing an MS in Data Science, a Data Analyst is one of the most sought-after positions. Data analysts are in high demand across a wide range of industries in Canada. | CAD 60,416 (Rs 35 lakh) |
| Data Mining Engineer | Demand for data mining engineers is growing quickly. In high-traffic transactional systems, they’re in charge of creating and evaluating data. After completing a Data Science programme in Canada, this is an excellent career path to pursue. | CAD 80,673 (Rs 47 lakh) |
| Machine Learning Engineer | After a Machine Learning Scientist, a machine learning engineer is the best option. In Canada, data-driven enterprises are thriving. Machine Learning engineers will be in high demand. If you want a good income, you’ll need to have an excellent grasp of programming languages, communication skills, data modelling, and analytics abilities. | CAD 140,000 (Rs 81 lakh) |
Data Scientists’ most sought-after skills
In order to become a data scientist, one must be familiar with a variety of programming languages. They must learn how to effectively communicate and interact with others.
- R programming • Hadoop platform • Python programming
- In addition, SQL databases are available.
- AI and machine learning
- Visualization of data
- Marketing plan for the company
Personality traits to have are:
- Communication is key.
- Storytelling skills are useful in statistical computations.
- Ability to work with different departments within a business.
- Understanding new ideas.
FAQs
Are data science jobs in demand in Canada?
Canadian data scientists earn more than their international counterparts on average. Students with a data science degree have a wide range of career options thanks to the high demand and adaptability of the field. According to the Canadian Bureau of Labor Statistics (BCLS), the annual compensation for a Data Scientist in Canada is CAD 95,000 (Rs 55 lakh).
Are artificial intelligence and data science promising careers?
Data science and artificial intelligence (AI) specialists are in high demand worldwide, making it an attractive career path. A professional can take advantage of significant career advancement prospects by becoming an AI engineer or data scientist.
Which course is best between data science and artificial intelligence?
If you’re interested in doing research, you should look into the discipline of data science. As an engineer, you should pursue a career in AI or machine learning if you wish to incorporate intelligence into software solutions.
What is the scope of data science and artificial intelligence?
A wide range of industries, from transportation and logistics to health care and customer service, will be impacted by advances in data science and artificial intelligence (AI) by 2025.
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