Employer demand for Data Scientist professionals is being driven by the need to analyze business intelligence data to inform organizational decision-making. This trend will accelerate as richer data sets become available and data analytics becomes a ubiquitous skill set across many business professions. Data Scientists utilize their analytical and programming skills to collect, interpret and analyze very large data sets in order to develop solutions to difficult business challenges. Data Scientists ultimately create algorithms and modelling processes that help businesses extract wanted data, then produce solutions to those challenges in order to optimize business functions and operations.
• The average Data Scientist salary in Canada is about $78,093.
• A Data Scientist typically makes anywhere between $53,000 - $115,000.
• An entry-level Data Scientist with less than 1-year of experience can expect to earn an average total compensation of $69,200.
Required Skills within Industry
• Overall, skills in Machine Learning, Python and Big Data Analytics are correlated to pay that is above the national average for this field.
• As many interfaces and businesses operate online, the ability to program is crucial to excel in this field.
• As businesses want to create solutions to ongoing issues, the ability to visualize data directly is essential as this will give you insights that will help your organization to act on new opportunities and stay ahead of competitors.
• Hence, a knowledge of probability and statistics is also essential in order to understand trends in data, relationships between variables, and anomalies that may lie within the data.
Salary Data and Skills retrieved from PayScale.
The Introduction to Data Science course allowed me to obtain new skills and knowledge of Data Science and R programming without interrupting my work schedule. Since the completion of the course, I’ve used these new skills to analyze data sets and provide timely solutions.
The course touched a lot of areas at a high level while also offering in depth labs to work through. That is something hard to balance in one course which this did perfectly. Since the course covered a lot of content ranging from what a data scientist is/does to understanding the concepts of machine learning, it helped me understand the scope of data science, introduced me to new tools and provided a way to collaborate with others on multiple data science projects.