We’re building a relationship-oriented bank for the modern world. We need talented, passionate professionals who are dedicated to doing what’s right for our clients.
At CIBC, we embrace your strengths and your ambitions, so you are empowered at work. Our team members have what they need to make a meaningful impact and are truly valued for who they are and what they contribute.
To learn more about CIBC, please visit CIBC.com
What you’ll be doing
We are seeking a Senior Data Scientist to drive the development of our AI-powered Marketing Engine, a critical capability in our journey towards a digital centric, world-class marketing vision. Reporting to Director, Marketing Data Science, this role will shape the way we engage customers through intelligent, real-time decisioning, ensuring every interaction is optimized for impact and relevance.
As part of this team, you will push the boundaries of AI-driven marketing, developing scalable machine learning solutions that power hyper-personalized experiences across omni channels. You will work cross-functionally to build a system that not only anticipates customer needs but delivers the right message at the right time – automatically and intelligently.
This is a unique opportunity to be part of a world-class AI-driven marketing transformation, where your work will directly shape how we connect with millions of customers. If you are passionate about AI, customer intelligence, and digital-first marketing, we’d love to hear from you.
At CIBC we enable the work environment most optimal for you to thrive in your role. You’ll have the flexibility to manage your work activities within a hybrid work arrangement where you’ll spend 1-3 days per week on-site, while other days will be remote.
How you’ll succeed
- Design & Develop Machine Learning Models - Leverage predictive modeling, optimization and reinforcement learning techniques to enable real-time customer decisioning.
- Own Model Deployment at Scale - Develop end-to-end ML pipelines, ensuring models are not just accurate but also fast, scalable, and production-ready.
- Leverage Big Data & AI Platforms - Utilize Databricks, Spark, and cloud-based ML tools to process large-scale customer interaction data.
- Ensure AI-Driven Marketing Activation - Partner with marketing, technology, and data teams to integrate AI seamlessly into digital and direct marketing campaigns and enable customer journeys.
- Drive Experimentation & Continuous Learning - Develop A/B testing frameworks to measure impact, iterate, and improve AI-driven recommendations.
- Contribute to a Digital-First Marketing Culture - Help bridge AI and business strategy, ensuring data science plays foundational role in our marketing transformation.
Who you are
- You have a Master's or PhD degree in a quantitative field required, or equivalent work experience.
- You can demonstrate 5+ years' hands-on experience in a data science or machine learning role, past experience with digital marketing domain is highly preferred.
- Strong development skills with proficiency in Python, Spark and advanced working SQL knowledge.
- Strong background in machine learning, reinforcement learning, optimizations. Past hands-on experience with recommender systems and uplift modeling is a plus.
- Hands-on experience with scalable cloud systems and cloud ML tools, preferably using the Azure stack and experience with Azure ML, Databricks, Azure Data Factory.
- Ability to build, deploy, and monitor ML models in real-world, high-impact environments, past experience is high preferred.
- Strong communication and partner management skills to connect ML innovation with marketing objectives, customer engagement, and ROI optimization.
- Passion for working in cross-functional teams and influencing AI adoption within a marketing-driven organization.
- Values matter to you. You bring your real self to work and you live our values - trust, teamwork, and accountability.
#LI-TA
What CIBC Offers
At CIBC, your goals are a priority. We start with your strengths and ambitions as an employee and strive to create opportunities to tap into your potential. We aspire to give you a career, rather than just a paycheck.
We work to recognize you in meaningful, personalized ways including a competitive salary, incentive pay, banking benefits, a benefits program*, defined benefit pension plan*, an employee share purchase plan, a vacation offering, wellbeing support, and MomentMakers, our social, points-based recognition program.
Our spaces and technological toolkit will make it simple to bring together great minds to create innovative solutions that make a difference for our clients.
We cultivate a culture where you can express your ambition through initiatives like Purpose Day; a paid day off dedicated for you to use to invest in your growth and development.
*Subject to plan and program terms and conditions
What you need to know
CIBC is committed to creating an inclusive environment where all team members and clients feel like they belong. We seek applicants with a wide range of abilities and we provide an accessible candidate experience. If you need accommodation, please contact [email protected]
You need to be legally eligible to work at the location(s) specified above and, where applicable, must have a valid work or study permit.
We may ask you to complete an attribute-based assessment and other skills tests (such as simulation, coding, French proficiency, MS Office). Our goal for the application process is to get to know more about you, all that you have to offer, and give you the opportunity to learn more about us.
Job Location
Toronto-81 Bay, 32nd FloorEmployment Type
RegularWeekly Hours
37.5Skills
Apache Airflow, Big Data Technologies, Communication, Critical Thinking, Data Analysis, Data Manipulation, Data Visualization, Machine Learning, Machine Learning Operations, Microsoft Azure Databricks, Optimization Models, PL/SQL (Programming Language), Predictive Modeling, Project Management, PySpark, Python (Programming Language), Reinforcement Learning, Stakeholder Management, Statistical Analysis, Strategic Thinking, Supervised Learning, Unsupervised Learning
