The pandemic has no doubt had some tremendous effects on the economies and job markets across all fields around the world. Now with working vaccines being rolled out worldwide and a hopeful return to more normal times, many are left with questions about the transformations of the industries and the future job market outlook.


In this month’s Lantern Roundtable series, we were joined by two senior professionals working in the data industry. Our first panel member was Tanaby Mofrad, a Director of Data Science at Tangerine Bank with a solid background in AI. Tanaby has worked on a variety of subjects, from signal processing to predictive models and price optimization. Our second panel member was Dr. Alireza Hojjati who got his Ph.D. in physics before joining the analytics team at Manulife and eventually moving onto his current position as a Senior Data Scientist at Genworth Financial.


  • Dr. Alireza Hojjati

Senior Data Scientist at Genworth Financial

  • Tanaby Mofrad

Director of Data Science at Tangerine Bank

The effects of the pandemic

To kick off the discussion we jumped right into it with a question about past and future. Around the end of 2019, there were reports predicting an increase of 2.3 million jobs in the data fields. As Covid-19 took hold of 2020, how did those predictions fare? Tanaby explained that while the market was moving in that direction the job market as a whole was certainly affected. Many companies took a conservative approach and tried to maintain the size and number of teams that already had. This meant throughout 2020 there were fewer likely fewer jobs as a whole and more competition to secure them. Alireza added that while the effects are largely dependent on the country and demographics, the tech industry suffered the least and in a number of regards actually saw growth as remote working and learning demanded new software support. Even though the market is not as hot as it was a year before the pandemic, it is starting to pick back up as companies and teams are trying to recover.

How has the industry evolved

Following up on that, our panel discussed how their respective industries and the data fields as a whole have changed in the last 5 years and what is predicted to happen in the next 5 years. Again, the answers for this are largely based on the type and size of the company rather than the data industry as a whole. In the past 5 years, big companies whether in banking or software or insurance were just getting started with incorporating data science into their business practices. The teams that were being put together were at the forefront of the development and professionals needed more traditional knowledge in general analytics and working with data. 

Now that those teams have grown and are established, their goals have evolved with new mandates and missions. The various responsibilities have now branched into various roles such as data engineer, cloud engineer, and cloud architect, to name a few. These roles are better defined than when the teams were first starting up and individuals performing them require niche skillsets. With that said, in addition to the data science teams the are pushing for new innovations and creating new branches of companies, the big companies also have a lot of legacy systems that are in dire need of upgrades. The companies are focusing on modernizing their processing and this will continue the demand for the skillsets we’re seen in the past.

Data Scientist vs Engineer vs Analyst

As we at Lantern get many questions from those looking to enter the data field, the panel were asked to give their take on the differences between typical roles in the industry and the traits that are sought after by hiring managers. Tanaby took the lead on this question and Alireza provided some additional notes.

Data Engineers mainly work with the platform and creation of the platform as well as preparing the data. This goes all the way from massaging the data to transforming the environments that hold the data. The goal of these tasks is to make it easier for data scientists to get the data and work with the data.

A Data Scientist starts by working directly with the data, spending 50-60% of their time working to transform and clean the data and to prepare it for modelling. Then they move onto the modelling phase which includes training models, validating the model, and tuning parameters of the model. On iterations of tuning parameters and testing the model, once it surpasses the required threshold it becomes ready for deployment. The deployment environment that is typically used nowadays is a cloud environment, either in-house or through third-party services like Amazon Web Services or Google Cloud Platform or Microsoft Azure. 

The responsibility of preparing these environments and choosing the right technologies falls to DevOps Engineers who make the whole platform ready for data scientists to use. Overall a Data Scientist needs extensive knowledge of machine learning and data analysis, as well as having broad knowledge for all the other parts and being able to perform the basic tasks of Data Engineers and DevOps Engineers.

There are many roles that often get lumped into the broad use of data science and tech jobs. Prospective professionals typically aim for jobs in data science without a clear idea of what they would like and what is available. Individuals should keep an open mind in their job hunting for more specialty roles and overlapping roles that are crucial components of the data science process.

Many more good topics we talked about throughout the panel event including answering some of the audiences pressing questions. If you missed the event and have your own questions you’d like to ask be frequently check back Lantern’s events page for more webinars to come. 

We would like to thank Alireza and Tanaby for sharing their insights and experiences, and we would like to thank the attendees for their interest in the event and for asking some great questions.

For those of you that are considering a career as a data professional and looking for a mentorship opportunity, reach out to Lantern and see if our programs are right for you.

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