Req Id: 431373
SummaryWe are looking for a Data Scientist, Marketing Analytics to join our team. In this role, you will be responsible for leveraging sales, marketing, and behavioral data to analyze and optimize marketing activities. This position will support a portfolio of marketing projects including marketing mix modelling, causal impact analysis, predictive modeling for customer acquisition and retention, lifetime value analysis, and more.
Key Responsibilities- Develop and maintain mathematical models to guide strategic business planning and marketing
- Develop and maintain continuous training predictive models for customer acquisition/retention
- Conduct statistical experiments to support a knowledge hub for strategic marketing insights
- Analyze, interpret, and present findings and recommendations to cross-functional business teams
- Collaborate with brand, marketing, and technical teams to translate business needs into solutions
- Participate in pilot programs to stay ahead of the curve in applied AI/ML advancements
- Support MLOps/DevOps for production model environments and process/test automation
- Clearly document your work and present concepts to both technical and non-technical audiences
- Participate in knowledge-transfer and cross-training to facilitate business continuity and resilience
Critical Qualifications- Bachelor's degree in a quantitative field (eg. Computer Science, Math, Statistics, Engineering)
- 3 + years of experience applying Data Science, Machine Learning, and advanced statistical modeling techniques to marketing analytics, customer acquisition, customer retention, customer segmentation, marketing measurement, or campaign optimization initiative
- Strong experience in data science, machine learning, research, and data pipeline development
- Proficient in data management and analytical programming languages (Python, SQL, R)
- Proficient using common data visualization packages and business intelligence tools
- Proficient using LLMs to judiciously expedite and automate tasks in a production environment
- Experience developing and maintaining data warehousing and data lake products
- Experience working with large marketing, media, behavioural, or cognitive data sets
- Experience working in secure corporate cloud environments (eg. GCP, AWS, Azure)
- Experience with constrained optimization models and statistical simulation methods
- Experience in applying both Bayesian and frequentist statistical concepts to large data sets
- Experience with analytical Python libraries (eg. TensorFlow, Keras, scikit-learn, pandas)
- Knowledge of agile project management philosophies and workflows
Adequate knowledge of French is required for positions in Quebec.
Additional Information:Position Type: Management
Job Status: Regular - Full Time
Job Location: Canada : Ontario : Toronto || Canada : Nova Scotia : Halifax || Canada : Ontario : Mississauga || Canada : Quebec : Montreal
Work Arrangement: Hybrid
Application Deadline: 07/26/2026
For work arrangements that are 'Hybrid', successful candidates must be based in Canada and report to a set Bell office for a minimum of 3 days a week. Recognizing the importance of work-life balance, Bell offers flexibility in work hours based on the business needs.
Please apply directly online to be considered for this role. Applications through email will not be accepted.We know that caring for our team members is at the heart of a healthy, positive and thriving workplace. As part of our team, you'll enjoy a comprehensive compensation package that includes a competitive salary and a wide range of benefits to support the well-being of you and your family. As soon as you join us, you'll be eligible for medical, dental, vision and mental health benefits that you can tailor to your specific needs. Plus, as a Bell team member, you'll enjoy a 35% discount on our services and access exclusive offers from our partners.
At Bell, we are proud of our focus on fostering an inclusive and accessible workplace where all team members feel valued, respected, supported, and that they belong.
Created: Canada, ON, Toronto
