Staff Data Scientist, (Global Security)

RBC; Toronto; On-site; CAD 90,000 - 120,000; Full time

Job summary

A leading financial institution in Canada seeks a Staff Data Scientist to advance its Global Cyber Security efforts. This role involves developing and deploying sophisticated machine learning models to combat digital threats, leading data science projects, and collaborating with various stakeholders. The ideal candidate holds an advanced degree and has proven expertise in machine learning and programming skills, particularly in Python. Opportunities include a comprehensive rewards program and dynamic teamwork.

Benefits

Comprehensive Total Rewards Program

Flexible benefits

Competitive compensation

World-class training program

Qualifications

• Strong theoretical foundation in quantitative fields.
• Proficient in developing and deploying complex machine learning models.
• Ability to communicate complex technical concepts effectively.

Responsibilities

• Lead complex data science projects from inception to completion.
• Collaborate with stakeholders to build advanced machine learning solutions.
• Design and implement end-to-end data pipelines for production.

Skills

Machine Learning

Statistical Modeling

Python

Data Mining Techniques

Deep Learning

Communication Skills

Education

Advanced degree in a quantitative field

Tools

AWS

Azure

GCP

PySpark

Job description

Overview

What is the opportunity?

We have an exciting opportunity in Global Cyber Security!

As a Staff Data Scientist in our team, you will lead the development and deployment of advanced machine learning models to proactively identify and mitigate evolving digital and cyber threats. You will collaborate closely with cross-functional teams to translate complex technical insights into actionable strategies, driving significant business impact and safeguarding RBC clients and data.

Data Science allows us to identify trends, anticipate malicious behaviors, perform pattern matching, discover new threats, and predict the outcomes of future events. Working as part of the Security Insights and AI, you’ll specialize in taking full advantage of large data sets to explore and discover new insights that would have not been possible with traditional analytics. Leveraging leading edge technologies and capabilities, you will apply machine learning and statistical modelling techniques to help RBC to proactively defend its digital information.

What will you do?

• Work closely with stakeholders to understand their needs and build solutions using advanced machine learning methods in the domains of fraud, cybersecurity, and data privacy
• Design and implement end-to-end data pipelines: from data cleaning to model development to writing production level code
• Lead complex data science projects from inception to completion
• Quickly learn new methods, big data tools and technologies presented in research communities to implement and adapt within our data products and models
• Collaborate proactively with various business and operation units to design innovative solutions to optimize processes and deploy production-scale solutions
• Work on challenging and research-based initiatives using advanced machine learning methods focusing on tangible outcomes
• Mentor and guide junior data scientists

What do you need to succeed?

Must have:

• Advanced degree in a quantitative field (e.g., Computer Science, Mathematics, Statistics, Engineering) with a strong theoretical foundation
• Proven expertise in developing and deploying complex machine learning models, including deep learning architectures, for solving challenging problems
• Highly proficient programming skills (Python, PySpark) and a deep understanding of statistical modeling, data mining techniques, and big data technologies
• Demonstrated ability to translate complex technical concepts into actionable insights and communicate effectively with both technical and non-technical stakeholders
• Passion for innovation and curiosity to explore emerging technologies and methodologies

Nice-to-have:

• Previous experience in cybersecurity/fraud domains
• Experience with MLOps to build end-to-end pipeline and deploying models in production
• Experience with graph analytics
• Experience with cloud platforms (AWS, Azure, GCP)

What’s in it for you?

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

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

Inclusion and Equal Opportunity Employment

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.

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Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at RBC.

Address: 330 FRONT 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: 2025-09-19

Application Deadline: 2025-09-30