What You’ll Do:
Support the development of machine learning models for offer personalization, customer propensity, next-best-product, and related use cases.
Explore, clean, and analyze large datasets to uncover insights and trends.
Build prototypes, run experiments, and contribute to model evaluation and validation.
Work with engineering teams to integrate models into production pipelines.
Help maintain and optimize existing ML workflows (Airflow, Dataproc, on-prem clusters, or cloud platforms).
Build dashboards and reports that communicate findings to business partners.
Participate in code reviews and follow team best practices.
What You Bring:
2+ years of experience in data science or applied machine learning.
Strong Python skills with exposure to ML libraries (e.g., scikit-learn, XGBoost, LightGBM).
Solid SQL skills and comfort working with large datasets.
Understanding of core ML concepts: regression, classification, validation, feature engineering.
Curiosity, problem-solving ability, and willingness to learn deeper modeling and production skills.
Ability to communicate analytical findings clearly and concisely.
Exposure to recommendation systems or marketing analytics is an asset.
Experience with A/B testing or experiment analysis is an asset..
Familiarity with Airflow, Docker, cloud compute (GCP/Azure), or distributed systems is an asset.
Knowledge of embeddings, uplift modeling, or personalization frameworks is an asset.
This posting represents an existing vacancy within our organization.
Data Scientist • Toronto, ON
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