Discovering Data Science Career Paths
Data science is one of the fastest growing STEM careers with high demand for skilled personnel to extract useful information from structured (e.g. databases, spreadsheets) and unstructured data (e.g. text, images, video, audio). Perhaps less well known is that job opportunities are not limited to big tech (e.g. FAANG); rather, companies across sectors as well as the public sector collect data and are building teams to help them derive insights.
Thus, in charting a career path, it is advisable to look beyond tech companies to the myriad opportunities in other sectors where data science is being increasingly integrated into operations. In fact, if job seekers focus narrowly on tech, they run the risk of missing a gamut of job openings for which their skill sets could apply.
Applied AI Lab Associate Perspectives
To gauge perceptions of applied data science career paths in the energy sector, we connected with some of our Associates partnered with Suncor for their impressions. Although they were generally aware, prior to joining the Applied AI Lab, that industrial sectors were starting to develop data science capabilities, the magnitude of the investment was a revelation. “Learning that Suncor has significantly increased their investment in their Advanced Analytics program really opened my eyes to how the energy sector is starting to transition into data science,” said Mitchell McCaig, AltaML Associate ML Developer. Similarly, Edwin Aguirre, AltaML Associate ML Developer, commented, “I was well aware of the potential for data science in traditional sectors, but it seemed to me that opportunities using data science were relatively slim.”
Indeed, they found opportunities they didn’t realize they had. So, to be able to capitalize on the growth of data science in the energy sector, how important is domain expertise, that is, a background in energy, in addition to data science expertise? Is it a prerequisite?
Our Associates weighed in that while energy expertise is undoubtedly an advantage, what is paramount is an ability to collaborate. As noted by Edwin, “My educational background and industry experience align very well with Suncor and having both domain expertise and data science experience are really important when trying to solve industry problems. However, if I had to choose, I would go with data science expertise, because data science logic can be applied to problems with input from domain experience professionals.” Similarly, Soheila Zanganeh, AltaML Associate ML Developer and M.Sc. student at the University of Calgary, observed that while she is new to the energy domain, she is having a good team work experience as a result of collaboration.
“We offer an opportunity for Associates to broaden their skill sets and work on technical problems that interface with classical engineering projects, which is both exciting and challenging at the same time,” says Tom Laskowski, Specialist Analytics Ecosystem, Suncor.
Overall, our Associates are galvanized by their experience so far which has revealed new opportunities. Soheila remarked that she recently realized the importance of a client-facing role to data science, noting, “I can see the necessity of professional communication skills to understand the problem.” Edwin noted, “after working with Suncor, I have seen how data science can be used to optimize engineering workflows, as well as geological based workflows, and that job opportunities will grow more and more!” And Mitchell is even more excited to work on real problems and affect real decision making.
To those looking for a career in data science, our Associates recommend getting started in demonstrating what you can do. “The field is huge, but there are numerous online resources to get started,” says Mitchell. “Learn to code (Python or R) and get a small dataset to play with and slowly move up to more complex datasets. Once you are confident, start a side project and post it to Github for the world (and future employers) to see!” Edwin advocates to “start working on your programming skills and data science skills, particularly visualizations and data storytelling.” And when you are job seeking, Soheila advises choosing companies that focus on learning and growing their employees.
Some final words of advice for new graduates, from Mitchell: “Even though the past year has been quite grim, data science is still a field that is growing faster and faster. Work hard and you will get to where you want to go!” We couldn’t agree more.
Artificial Intelligence and Advance Analytics at Suncor
Our digital transformation is underway
Suncor is on a transformational journey that is part of our next chapter of growth and energy transition. We are leveraging data to drive value and using digital tools and technology to change how we do business.
As part of our approach, we’re harnessing digital capabilities —including AI—to help improve the safety, reliability and environmental performance of our operations.
Leveraging advanced analytics at Suncor
Advanced Analytics plays a key role in our transformation journey and is bringing people and science together to solve business problems. We are leveraging AI/ML to increase effectiveness and efficiency by creating and enhancing tools that already exist and investing in analytics technologies and partnerships, such as our strategic alliance with Microsoft as our cloud solution provider, to build a strong infrastructure to support our work.
By applying advanced analytics to initiatives from the business, we are able to gain new insights that deliver value and allow us to take action and apply our learnings across the organization. Leveraging analytics is one way we are becoming a data-informed enterprise where analytics is a persistent capability and everyone can apply their knowledge, draw insights and make the best possible decisions.
Building our AI talent pipeline
Suncor is building the most innovative analytics team within the global energy industry. Our strategy is ambitious: we intend to create hundreds of millions of dollars in realized value for Suncor within five years.
Through upskilling, reskilling, hiring new talent and collaborating with key partners — like the AltaML AI LAB — we are creating a dynamic, diverse team that explores and solves business problems using literally billions of data points. With an integrated corporate model, the array of opportunities is vast —from mining to supply chain, refineries to Petro-Canada sales and marketing, or energy trading to health and safety. The variety of challenges we’re asked to solve is extraordinary.
If you are interested in joining Suncor’s advanced analytics team, you can review and apply to any upcoming opportunities on our career site at www.suncor.com/careers. You can also sign up for job email alerts based on job category and location with your Candidate Profile, to ensure you never miss an opportunity!
New opportunities with the AI Lab
Our partnership with the AltaML AI Lab provides real-world opportunities to leverage data to support advanced analytics, timely decisions and efficiency in our teams. Interns are working to solve Suncor problems with Suncor data, which should positively impact our business. For example, we are using AI to examine how we can extend the life of our operating assets through predictive maintenance and improve our communication with stakeholders. We also offer opportunities to develop and enhance other skills, such as presentations and showcases to various stakeholder groups.
About the Applied AI Lab
The Applied AI Lab was created to accelerate applied AI development through a machine learning and data science internship. The AI Lab is a collaborative industry-led initiative, partnering with ATB, Suncor Energy, Spartan Control, and TransAlta. It helps bridge the talent gap between academic and applied skills by providing interns with guidance and access to real business problems, data, and industry partners. Over the 3-year program term approximately 240 individuals will have the opportunity to gain hands-on experience in applying AI.
For more information contact:
Danielle Gifford, Senior Manager of the Applied AI Lab
