Data Engineer jobs in Canada

RBC Technology Infrastructure seeks a full stack Data Scientist (DS) to explore and operationalize big data sources to reduce outage and downtime for RBC services that leads to improve user experience and save costs. Seeking a DS with experience in applied research and problem solving to join our team. The successful candidate will have experience with developing and deploying production grade AI/ML solutions, have broad expertise in statistics, analytics, ML and strong programming skill.

• Lead full life-cycle Data Science solutions from beginning to model deployment and monitoring and partner with the engineering team to ensure best practices for ML model deployment.
• Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement.
• Experience in (Python, Apache Spark, PySpark, R, Scala, SQL, NoSQL, etc.) to obtain, integrate, manipulate, and analyze data from multiple sources.
• Expertise in statistical data analysis (e.g. univariate/bivariate analysis) and data quality assessment.
• Build Machine Learning, Deep Learning and statistical models to solve specific business problems.
• Develop predictive data models, anomaly detection model, quantitative analyses and visualization of targeted big data sources.
• Lead data exploration and analytic projects and provide ongoing coaching on big data topics (visualization, data mining, analytic techniques).
• Explore and implement semantic data capabilities through NLP, text mining and machine learning techniques.
• Oversee the acquisitions and ingestions of data from structured and unstructured sources, while ensuring quality and comprehensiveness of data.
• Utilize APIs to collect data from various products into the Data Warehouse Database.

Must have:

• 5+ years of industry experience required working on real-world problems
• University, Master or Ph.D. degree in an analytical field of study (e.g. Computer Science, Engineering, Mathematics, Statistics, or related quantitative field)
• Experience working with technical and non-technical project stakeholders to scope, formulate, deploy, and maintain data science systems.
• Self-driven problem solver, able to adapt and thrive in a dynamic, ambiguous, and customer‑faced environment.
• Strong communication, collaboration, and problem‑solving skills.
• Ability to prioritize work and manage multiple work streams concurrently.
• In‑depth knowledge in machine learning and deep learning algorithms.
• Excellent working with structured and non‑structured data.
• Excellent knowledge in Python, PySpark, SQL.
• Experience with cloud‑based data platforms such as Azure or AWS.
• Experience with data visualization tools such as Tableau, Looker, and Power BI.

• Experience architecting large scale ML systems.
• Experience working knowledge of Reinforcement learning (DynaQ/Q+, SARSA, TD, Monte Carlo).
• Experience with GenAI LLM models.
• Experience with MLOps workflow.
• Knowledge in AIOps domain.
• Knowledge of IT Operation Monitoring Tools (Dynatrace).

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable
• Leaders who support your development through coaching and managing opportunities
• Ability to make a difference and lasting impact
• Work in a dynamic, collaborative, progressive, and high‑performing team
• A world‑class training program in financial services
• Opportunities to do challenging work
• Opportunities to take on progressively greater accountabilities
• Opportunities to building close relationships with clients
• Access to a variety of job opportunities across business and geographies.

Actuarial Modeling, Big Data Management, Commercial Acumen, Data Mining, Data Science, Decision Making, Machine Learning (ML), Natural Language Processing (NLP), Predictive Analytics, Python (Programming Language)

Address: RBC CENTRE, 155 WELLINGTON ST W:TORONTO

City: Toronto

Country: Canada

Work hours/week: 37.5

Employment Type: Full time

Platform: TECHNOLOGY AND OPERATIONS

Job Type: Regular

Pay Type: Salaried

Posted Date: 2025-12-12

Application Deadline: 2025-12-31

Applications will be accepted until 11:59 PM on the day prior to the application deadline date above.

At RBC, we believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.