Hiring Data Scientists in Canada’s Banking, Finance, and Insurance Sectors
The role of data scientists in Canada’s banking, finance, and insurance sectors has become increasingly critical as financial institutions embrace digital transformation, artificial intelligence (AI), and big data analytics. This report provides a detailed quantitative and qualitative analysis of employment trends for data scientists in these sectors up to 2030. The report draws on multiple data sources, including the Canadian Business Patterns (CBP), Labor Force Survey (LFS), Survey of Employment, Payroll, and Hours (SEPH), and Canadian Occupation Projection System (COPS).
As the industry pivots towards data-driven decision-making, data scientists are expected to be at the forefront, analyzing complex data to guide risk management, fraud detection, customer insights, and personalized financial products. The report explores how demand for these roles will evolve with advancements in machine learning and regulatory pressures around data governance and cybersecurity. It also examines the skills that will be most in-demand, including expertise in predictive analytics, natural language processing, and ethical AI.
Furthermore, the analysis highlights emerging challenges, such as talent shortages, wage inflation, and the need for continuous skill development to keep up with rapid technological change. This outlook underscores the importance of strategic workforce planning and investment in training programs to build a pipeline of qualified data scientists who can meet the sector's growing needs.
Key Findings – 2030 Projections
By 2030, the number of professionals employed in Canada’s banking, finance, and insurance sectors is expected to surpass 10,000, driven by demand for advanced skills in AI, machine learning, and big data. Wages will see notable increases, with the median salary rising from CAD $110,000 to $130,000, reflecting both market demand and the specialized skill sets required.
Additionally, up to 1,000 new job openings will emerge from retirement alone, ensuring a steady influx of positions. These openings will not only be in major hubs like Toronto, which is projected to employ over 7,500 data scientists, but also in other growing regions such as Ottawa and British Columbia. The competition for talent will be fierce, with Canadian institutions contending with global firms, influencing both recruitment strategies and salary benchmarks.
Key Findings – 2030 Skills
Educationally, data science professionals in finance will increasingly hold master’s degrees or higher, with over 85% of new hires expected to have advanced degrees by 2030. The rise of AI and data analytics will necessitate constant upskilling, making continuing education a key component for both retention and job security in these sectors. The most sought-after skills will include:
Machine Learning and Predictive Analytics: To power AI-driven decision-making.
Natural Language Processing (NLP): For interpreting and leveraging unstructured data.
Ethical AI Practices: Addressing concerns around fairness, transparency, and bias in algorithms.
Conclusion and Future Outlook
The future landscape for data scientists in Canada’s banking, finance, and insurance sectors is defined by significant quantitative shifts across multiple dimensions. By 2030, the number of professionals employed in these sectors is expected to surpass 10,000, driven by demand for advanced skills in AI, machine learning, and big data. Wages will see notable increases, with the median salary rising from CAD $110,000 to $130,000, reflecting both market demand and the specialized skill sets required.
Moreover, up to 1,000 new job openings will emerge from retirement alone, ensuring a steady influx of positions. These openings will not only be in major hubs like Toronto, which is projected to employ over 7,500 data scientists, but also in other growing regions such as Ottawa and British Columbia. The competition for talent will be fierce, with Canadian institutions contending with global firms, influencing both recruitment strategies and salary benchmarks.
Educationally, data science professionals in finance will increasingly hold master’s degrees or higher, with over 85% of new hires expected to have advanced degrees by 2030. The rise of AI and data analytics will necessitate constant upskilling, making continuing education a key component for both retention and job security in these sectors.
In summary, the quantitative growth in employment, salaries, and educational requirements highlights a robust future for data scientists in Canada’s finance sectors, driven by technological advancements and the digital transformation of financial services.
About Robertson RPO
Robertson RPO is an outsourced recruitment partner that leverages the latest tools, technologies, and data-driven strategies to streamline hiring, enhance candidate quality, and build sustainable talent pipelines that keep organizations competitive and agile. With 15 offices in North America, our clients have unprecedented access to thought leadership, industry executives, and best-in-class delivery and service.
Contact: Maria Arvanites, VP, Robertson RPO T: 647-669-3378 E: maria.arvanites@robertson.ca or visit the contact page.