what is a data scientist?
Companies, governments and other institutions rely on data more than ever to make decisions. This data can track everything from traffic flows to consumer purchasing habits and weather patterns. However, raw data doesn't help decision-makers choose the best options; someone has to process and analyze it. This task falls to data scientists. As a data scientist, you are an expert analyst with deep knowledge of technology and statistics.
Data scientists combine their analytical skills with knowledge of the topic they're analyzing to create models based on the data they study. Data scientists use these models to understand past and present situations and predict future behaviour.
Like all scientists, data scientists conduct analyses and present their findings to others. Whether that means communicating with corporate management, the government or the public, data scientists provide clear and useful information. This means that communication skills are vital to a data scientist's job.
Would working as a data scientist suit your analytical and problem-solving skills? Then read on to find out what competencies and qualifications you need to thrive in a data scientist role.
data scientist jobsaverage data scientist salary
According to Job Bank, the average earnings of a data scientist is $136,494 per year. The take-home salary fluctuates based on your experience, qualifications and skills. In an entry-level position, you start with an annual salary of $124,960. You have minimal experience and often work in a supporting role, but as you gain experience, your take-home salary increases to over $140,000 annually. Your earnings also fluctuate based on location. For instance, in Nova Scotia, you receive an average salary of $137,715 per year, while in Manitoba, your average salary is $86,085 yearly.
how to increase the salary of a data scientist
You can increase your earnings by gaining additional certifications and educational qualifications. If you have a degree, getting a master's and professional certifications improves your salary expectations. Gaining experience also improves your earning potential. Most employers have high salary ranges for data scientists with vast experience and skills.
Some specializations also attract higher salaries. For instance, the demand for data engineers and database management system (DBMS) architecture specialists increases the salary expectations in the role. Specializing in high-demand areas improves your earnings significantly.
types of data scientists
Within the world of data science, you can pursue different specializations. These include:
- data engineering: a data engineer builds and maintains the frameworks used for analysis by consolidating, cleansing and structuring data collected from multiple sources.
- database management and architecture: a step up from a data engineer, this type of specialist is responsible for designing the digital framework of a specific organization.
- operations data analysis: less technical than other data scientist roles, an operations data analyst uses statistical software to evaluate and solve business-specific problems.
- marketing data analysis: a marketing data analyst is concerned with measuring and improving the effectiveness of a marketing campaign, particularly in terms of ROI and with consideration of marketing trends.
- machine learning: a growing field within data science, data scientists specializing in machine learning (ML) create algorithms that work without direct human participation. Automated ML systems can work many times faster than humans, making them ideal for large data sets.
- artificial intelligence: artificial intelligence (AI) is another specialist area within data science. Although related to ML, AI has its methods and principles, and many data scientists specialize in one or the other.
working as a data scientist
Do you have an analytical mind and are interested in finding out what a job in data science involves? Here, you will discover the daily duties, career opportunities and work schedules of a data scientist.
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what does a data scientist do?
As a data scientist, you use your knowledge of math, statistics and analytical methods to understand data sets. Your work includes:
- researching an industry or company: as a data scientist, you research an industry or company to identify trends and pain points. You use the information to find opportunities for growth in your company. Your job also involves identifying inefficiencies in the production process and developing ways to improve productivity.
- defining relevant and useful data sets: before making conclusions from your findings, you define the data sets relevant to your research. You set the parameters for the research to make it easier to study trends and patterns in the datasets. When you have defined the data sets for your research, you extract data and collect information from various sources.
- cleaning data collected: data extracted from various sources may not give accurate conclusions if it is not analyzed. As a data scientist, you clean the data to remove anything unusable and then test it to ensure it's relevant to the research.
- creating algorithms and data models: as a data scientist, you develop the algorithms for data forecasting and use them to analyze data and identify latent trends or patterns. You also create automation tools that simplify the data collection and analysis process.
- visualizing data and presenting findings: after analyzing data trends, you visualize the data and organize it into dashboards for easy reading. When you organize the findings, you make them accessible to decision-makers. As a data scientist, you also make recommendations on areas of improvement in the organization.
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work environment of a data scientist
As a data scientist, you typically work in an office environment. Most of your analysis is done using computers and other information technology (IT) tools. Your job may involve some travelling to attend meetings or conferences, but regular travel is uncommon. You may not even work in a traditional office. Increasingly, many data scientists work remotely, either going into the office occasionally or working entirely online.
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who are your colleagues?
Depending on your employer and the industry you work in, your colleagues might include data analysts, business systems analysts and business analysts F&A. You work with analysts to help them create algorithms for analyzing the data collected. You also work with other professionals, such as engineers, economists and computer experts. You collaborate with social media managers, web developers and financial analysts to collect data used in research. Other specialists you are likely to work with include research scientists and market research executives.
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data scientist work schedule
A data scientist's schedule is relatively predictable. Most often, you work regular office hours during the week. Late hours and weekend work are rare. Additional evening hours may be required as a project deadline approaches. A certain amount of flexibility in working hours is therefore expected of this job, as submitting reports or other similar publications is one of the important tasks of a data scientist. On average, you are expected to work between 37 and 39 hours per week.
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career opportunities as a data scientist
Your career as a data scientist offers excellent prospects for advancement due to the high demand for the role. In addition to going deeper into data science through experience and postgraduate study, you can move into other fields. You could specialize in a specific area of data science, such as machine learning. If you enjoy working with large teams of data scientists, consider moving into a management or project management role. If you're more focused on the science side of your work, consider a move into academia as a researcher or lecturer.
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advantages of finding a job as a data scientist through randstad
Working with Randstad offers you a range of benefits.
- always a contact person you can fall back on and ask for help from
- many training opportunities
- a range of jobs in your area
data scientist skills and education
If you are interested in becoming a data scientist, you require the following qualifications:
- get a bachelor’s degree: to become a data scientist, you require a bachelor’s degree in mathematics, computer science, computer systems or statistics. You can also complete a college program in computer science.
- pursue a master’s or doctoral degree: most employers expect data scientists to have a master's or doctoral degree in machine learning or a quantitative field. Having additional educational qualifications improves your career prospects.
- work experience: you require experience in statistical modelling or machine learning to work as a data scientist. Some of your duties need knowledge of programming fundamentals, which you can learn through professional certifications.
competencies and characteristics of data scientists
Some of the highly desired skills and competencies of a data scientist include:
- programming skills: you require proficiency in programming languages to excel as a data scientist. For instance, you need knowledge of Python, SQL and Java to develop and implement complex algorithms and models. With your programming skills, you can sort, analyze and manage large chunks of data using various modelling and visualization techniques. Polish your programming skills through online courses and boot camps.
- communication skills: as a data scientist, your communication skills are crucial. You cannot communicate findings and recommend changes without communication and presentation skills. Your ability to share your ideas in written language or verbally is critical to success.
- data analytics: your job involves analyzing large volumes of data to identify trends and patterns. With your analytical skills, you easily understand data and extract meaningful insights. You can perform predictive modelling and data visualization.
machine learning: as a data scientist, you incorporate machine learning and deep learning (DL) into data visualization to improve the quality of data gathered. A course in machine learning helps you predict outcomes in future datasets.
FAQs about working as a data scientist
Here, you will find the answers to the most frequently asked questions about the profession of a data scientist.
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are data scientists in demand in Canada?
Canada's increased focus on innovation and technology has given rise to many tech companies. Hence, there is a demand for data experts in technology companies and businesses in other industries. Aside from private companies, there is also a huge demand for data scientists in government sectors.
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is a data science career worth it?
With great prospects for growth, data science is a promising career in Canada. It is also a lucrative career with an attractive salary and good opportunities for promotions. When you start in an entry-level position, you'll progress to mid-level and top positions after working in the field for a few years.
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how much do data scientists make?
As a data scientist, you make an average salary of $136,494 per year, which equals an hourly rate of $70. Your earnings are slightly lower at an entry-level position, while experienced data scientists take home over $140,000 per year. The salary depends on experience and qualifications.
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what skills do you need to be a data scientist?
To work as a data scientist, you require modelling and analytical skills. You analyze large volumes of data and derive information useful in decision-making. Your ability to present and communicate your findings is also crucial.
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how do you become a data scientist?
The minimum entry requirement for a data scientist is a bachelor’s degree in data science, computer science or statistics. In some industries, you may also need a master’s or doctorate qualification.
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how do I find a job as a data scientist?
Finding a job near you as a data scientist is easy. Search our job offers. Have you found what you're looking for? Then submit your application using the 'Apply' button top right on the page. No jobs available right now? Send us your resume, and we'll pass it on to a recruiter who will contact you if an opportunity opens up for you.
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