Manager, Data Scientist
- Toronto, ON, Canada
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Job details
- Experience
- 5 to 8 years of experience in Data Science, Machine Learning, Applied AI, or Advanced Analytics.
- Posting language
- English
- Posted
Original job description
We are committed to connecting Canadians through unique partnerships, our world-class network and content Canadians love - and our innovative team is growing. We are looking for dedicated team members to join our Corporate team who have a genuine passion for making positive impacts on customers and the communities where we live and work. We have a variety of business units with exciting and meaningful work waiting for you, including Communications, HR, Legal and Corporate Affairs, Supply Chain, Finance, and Real Estate. If you are considering your next step, we have exciting opportunities waiting for you. Come build a rewarding career at Rogers and be a driving force behind our success story!
Who we're looking for:
We are looking for an experienced Data Scientist to join our team and help build, deploy, and optimize machine learning solutions that influence decisions across millions of customer interactions. Our team manages a large enterprise model portfolio supporting customer acquisition, retention, and lifecycle marketing. You'll work extensively within our Databricks and Azure based machine learning environment using Python, Spark.
This is a highly hands-on individual contributor role for someone who enjoys owning the full model development lifecycle, from business problem definition and feature engineering to production deployment and performance monitoring. You'll work closely with business stakeholders, data engineers, and fellow data scientists to deliver measurable business value through advanced analytics and machine learning.
What you'll do:
- Build Production Machine Learning Models
- Design, develop, validate, and deploy predictive models and machine learning solutions.
- Perform feature engineering, model selection, hyperparameter tuning, and model evaluation.
- Monitor deployed model performance and recommend enhancements as business conditions evolve.
- Deliver models that are scalable, maintainable, and production-ready.
- Design and evaluate experiments, A/B tests, champion-challenger frameworks and model performance assessments to measure business impact.
- Solve Business Problems
- Partner with business stakeholders to identify, prioritize, and size opportunities where advanced analytics and machine learning can drive measurable business outcomes.
- Translate ambiguous business objectives into structured analytical approaches, clear success metrics, and actionable recommendations.
- Perform exploratory analysis to uncover customer behaviors, business trends, risks, and opportunities within large and complex datasets.
- Collaborate with stakeholders to define success criteria, quantify business impact, and ensure analytical solutions are adopted and utilized in decision-making processes.
- Present analytical findings, model results, and strategic recommendations to both technical and non-technical audiences in a clear and compelling manner.
- Work Across the Full ML Lifecycle
- Develop reusable code, data assets, and model components.
- Collaborate with Data Engineering and MLOps teams on deployment and operationalization.
- Support model governance, documentation, validation, and monitoring processes.
- Contribute to continuous improvement of data science best practices.
- Collaborate and Innovate
- Collaborate with stakeholders to define success metrics, quantify business impact and ensure analytical solutions drive measurable outcomes.
- Work with cross-functional teams including Marketing, Product, Technology, Data Engineering, and Analytics.
- Share knowledge and mentor junior team members when appropriate.
- Stay current with emerging machine learning and AI technologies and identify opportunities for practical application.
- Explore and apply Generative AI, large language models and emerging AI technologies where they provide practical business value.
What you bring:
- Experience
- 5 to 8 years of experience in Data Science, Machine Learning, Applied AI, or Advanced Analytics.
- Experience developing propensity, churn, customer segmentation, recommendation, next-best-action, offer optimization models in production environments is highly desirable.
- Proven experience developing and deploying machine learning models in production environments.
- Experience solving real-world business problems using data and analytics.
- Technical Skills
- Strong programming skills in Python, SQL, and Spark for large-scale structured and unstructured data analysis and machine learning development.
- Experience using Git-based development workflows, including version control, branching strategies, code reviews, pull requests, and collaborative development practices.
- Hands-on experience with machine learning frameworks and libraries such as Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch.
- Strong understanding of feature engineering, model evaluation, experimentation, statistical analysis, and predictive modeling techniques.
- Hands-on experience with model deployment, MLOps, CI/CD pipelines, Azure and Databricks is strongly preferred.
What’s in it for you?
We believe in investing in our people and helping them reach their potential as valuable members
of our team. As part of our team, you’ll have access to a wide range of incredible resources, growth
opportunities, discounts, and perks, including:
- Competitive salary & annual bonus.
- Competitive & flexible health and dental benefits, pension plan, RRSP, TFSA, and Stock matching programs.
- Discounts: Enjoy up to 50% off Rogers Services and Blue Jays Tickets, 25% off TSC items, and a 20% discount on all wireless accessories sold in Rogers stores.
- Paid time off for volunteering.
- Company matching contributions to charities you support.
- Growth & Development Opportunities:
- Self-driven career development programs.
- Rogers First: priority in applying to internal roles of interest.
- Wellness Programs:
- Employee & family assistance program.
- Virtual Healthcare.
- Cognitive Behavioural Therapy (CBT).
- Low or no-cost fitness membership.
- Our commitment to diversity:
- An inclusive and diverse workplace where you can bring your whole self to work.
To protect our people, brand and assets, a pre-employment background check will be conducted. As part of our selection process, all candidates must clear a criminal background check. Additionally, a credit check and drivers abstract may be required depending on the role.
Schedule: Full time Shift: Day Length of Contract: Not Applicable (Regular Position) Work Location: 1 Mount Pleasant (083), Toronto, ON Travel Requirements: Up to 10% Background Check(s) Required: Canadian Criminal Record Check Posting Category/Function: Digital & Advertising & Analytics Requisition ID: 341598
To support career growth, collaboration, and high-performing teams, all Corporate Employees are expected to work onsite. We believe that in-person connection strengthens our culture and drives industry-leading performance.
At Rogers, we believe the key to a strong business, is a diverse workforce where equity and inclusion are core to making everyone feel like they belong. We do this by embracing our diversity, celebrating our different perspectives, and working towards creating environments that empower our people to bring their whole selves to work. Everyone who applies for a job will be considered. We recognize the business value in creating a workplace where each team member has the tools to reach their full potential by removing any barriers for equal participation. We work with our candidates who are experiencing a disability throughout the recruitment process to ensure that they have what they need to be at their best. Please reach out to our recruiters and hiring managers to begin a conversation about how we can ensure that you deliver your best work. You matter to us! For any questions, please visit the Recruitment Process FAQ.
Posting Notes: Corporate
More about this job
Responsibilities
Design, develop, and deploy scalable machine learning models to drive business outcomes across customer interactions. Collaborate with cross-functional teams to translate business objectives into structured analytical approaches and actionable recommendations.
Requirements
Requires 5 to 8 years of experience in data science or machine learning with strong proficiency in Python, SQL, and Spark. Proven experience in production-level model deployment and MLOps within Azure and Databricks environments is essential.
Skills
- Python
- SQL
- Spark
- Databricks
- Azure
- Machine learning
- Predictive modeling
- Feature engineering
- MLOps
- Git
- Scikit-learn
- XGBoost
- LightGBM
- TensorFlow
- PyTorch
- A/B testing
Benefits
- Competitive salary
- Annual bonus
- Health benefits
- Dental benefits
- Pension plan
- RRSP
- TFSA
- Stock matching programs
- Employee discounts
- Paid time off for volunteering
- Company matching contributions to charities
- Career development programs
- Employee and family assistance program
- Virtual healthcare
- Cognitive behavioural therapy
- Fitness membership
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Management & Leadership
Keywords
- Data Science
- Machine Learning
- Applied AI
- Advanced Analytics
- Python
- SQL
- Spark
- Databricks
- Azure
- Git
- Scikit-learn
- XGBoost
- LightGBM
- TensorFlow
- PyTorch
- MLOps
- CI/CD
- Feature Engineering
- Predictive Modeling
- A/B Testing
- Generative AI
- Large Language Models
- Propensity Modeling
- Churn Analysis
- Customer Segmentation
- Recommendation Systems
- Offer Optimization
- Statistical Analysis
- Model Governance
- Data Engineering