Due to the advancement in data science technology, data scientists are in high demand. Here’s an article by Latha Jishnu on the latest job opportunities that you can look out for if you’re planning to immigrate or have already moved to Canada under Federal Skilled Worker Program (FSWP) and Canadian Experience Class (CEC) categories.
Data Scientist, Risk Analyst, Business Intelligence Developer, Data Analytics Consultant – where do I start? Hello everyone! Today I am writing about all those new career opportunities one can find after having permanent residency in Canada. Since my last article for the Canadian way was well received, it has inspired me to write about some more job opportunities that we can find across various cities in Canada. I am currently on an H-1B visa and moving towards permanent residency this year.
With the help of my career counselor, I have identified a few such jobs that match my skill set and make it easier for me to understand the requirements of employers better and hence be able to navigate through the whole process easier.
Data Scientist –
This profession came into existence basically because of all those large data sets available there. Companies wanted people who could work with them and derive meaningful insights from those datasets. This made me think about what exactly is a Data Scientist? A Data scientist builds mathematical models and machine learning algorithms to solve business problems using existing data sets. For example, suppose the task is to recommend movies based on our likes and dislikes. In that case, one can use an algorithm that mines through your previous purchase history and preferences to calculate your likely rate of returning for another movie. Another usage could understand market trends by collecting various user behavior patterns, which helps in the effective business decision-making processes or marketing campaigns.
Risk Analyst –
Another new profession that is gaining popularity day by day is a Risk Analyst. The risk analyst can be found working in various industries like, for example, financial services and insurance, healthcare and pharmaceuticals, etc., wherever there’s high volume and evolving regulatory requirements, one has to ensure compliance and mitigate the risks associated with it. So a risk analyst works across all these departments to design strategies and controls to enable effective management of compliance threats while mitigating the risk involved. Where I come from (India), we have had such professionals who work closely with auditors, but I am not sure if Canada follows this practice.
The data science industry is booming, and the demand for talented data scientists has never been higher. While it’s great to see such an increasingly large demand for people with these skills, there are a couple of challenges you’ll need to consider before embarking upon this career path.
Thrown into the Deep End
While learning new technologies might come relatively easy to some, mastering the art of collecting, cleansing, integrating, and presenting big data can prove quite challenging if you’ve never done it before. The good news is that you don’t necessarily need any industry experience or even a degree in computer science or mathematics. Still, you will have no choice but to jump in at the deep end when trying to find your Data Science position. Even if you have the necessary skills, you’ll need to show your potential employer how much you know in your CV or application form to convince them that you can do the job. One way of doing this would be by taking online courses available through MOOCs (Massive Open Online Courses). While these won’t guarantee that you get hired straight away, they will at least help you pass an interview.
The Pay-Off
One advantage of having gained experience working in data science is that your paycheck will start looking a lot healthier once you’re hired! According to Glassdoor.com, data scientists’ average annual base salary currently stands at $96,240. However, if we consider bonuses and commissions earned over the year, that figure is usually much higher.
Conclusion:
While it’s clear that there are significant benefits associated with working as a data scientist, it’s also worth noting that you will need to invest time and effort into learning new skills before you can start applying for jobs. It may take you several months or even years before you become an expert but never forget that this is not just about learning how to program using Python or R. You’ll also need to familiarize yourself with your programming tools, databases, and other technical concepts related to collecting, cleaning and preparing your data. In addition, presenting your findings clearly and persuasively will only come with.
