Data Scientist applying machine learning models to solve complex business problems. Collaborating on cross-functional projects to benefit internal stakeholders at CBC/Radio-Canada.
Responsibilities
Identify, clean, transform and synthesize large volumes of data within our Big Data environment or using our analytical tools.
Help verify and validate data to ensure input quality and model reliability.
Contribute to the preparation, enrichment and transformation of user-level engagement data, and build scalable data processing pipelines.
Select and apply appropriate modelling techniques to achieve audience segmentation and customization goals.
Leverage machine learning models to automate solutions to complex challenges.
Develop and implement marketing attribution models (e.g., marketing mix modelling).
Conduct content affinity analyses (e.g., market basket analysis) to uncover relationships between assets.
Leverage artificial intelligence techniques to analyze complex data and enhance customization and automation capabilities.
Partner closely with the Big Data Development and Data Integration teams to define data collection strategies.
Present analyses and insights to a diverse internal audience, including product managers and marketing/communications managers.
Establish team-wide analytical best practices by designing technical templates and documentation.
Create and maintain Power Platform solutions (Power BI, Power Automate) to provide internal teams with self-service access to model insights.
Maintain strong relationships with corporate clients as an internal consultant.
Monitor changes in source data structures and analyze their impact on existing models.
Requirements
Minimum five years’ experience in a similar data science role.
Graduate degree in a relevant field (business intelligence, economics, mathematics, statistics, IT, etc.).
Good knowledge of statistics.
Advanced proficiency in SQL and Python (pandas/PySpark).
Familiarity with web analytics and A/B testing platforms (e.g., Google Analytics, Adobe Analytics).
Deep understanding of marketing measurement (attribution, lift studies, etc.).
Experience creating marketing mix models (MMM).
Proficient knowledge of machine learning (experience using multiple advanced analysis techniques or machine learning algorithms).
Experience using k-means clustering and SVM classifiers an asset.
Knowledge of MLOps (MLFlow).
Practical, hands-on experience working with GenAI models.
Good knowledge of Power BI (visual design and DAX; PowerQuery/M an asset).
Knowledge of data management platforms (DMP/CDP) and their APIs an asset.
A proactive, consultative mindset when working with internal clients.
Ability to explain statistical concepts to non-experts.
Ability to work as a team player.
Media industry experience an asset.
Familiarity with CBC/Radio-Canada platforms and content an asset.
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