Marketing Data Scientist

12 month contract

Hybrid 2x per week in Toronto

Pay: $70-77/hr incorp

Required Skills & Experience

• 3+ years of technical experience
• Strong proficiency in Python and experience with open-source MMM packages.
• Experience with AWS, specifically SageMaker.
• Previous experience in building and implementing marketing mix models.
• Strong analytical skills with the ability to interpret data and make informed decisions.
• Excellent communication and collaboration skills.

Nice to Have Skills & Experience

• Experience in the retail sector, although banking or large enterprise experience is not required.
• Familiarity with high-visibility projects sponsored by executive-level stakeholders.

Job Description

Insight Global is seeking a highly skilled and inquisitive Marketing Data Scientist to join our banking client's North American Marketing Data Science team. This role will be pivotal in advancing their in-house capabilities in Marketing Mix Modeling (MMM), experimentation, and multi-touch attribution (MTA). The ideal candidate will have hands-on experience with open-source MMM tools, and will be passionate about translating complex data into actionable insights that drive smarter media investment and marketing optimization.

This is a hybrid role and requires 2x/week downtown Toronto (Wednesday and Thursday preferable).

Key Responsibilities

• Lead the development and implementation of in-house MMM solutions using open-source packages (e.g., Google Meridian, PyMC).
• Consults on analytical solutions to understand, analyze, and synthesize business requirements, enabling high-quality, fact-based decisions that drive better marketing outcomes and support strategic initiatives.
• Clean, aggregate, and transform raw data from media, sales, pricing, promotions, macro signals, etc. Ensure time alignment, lag structures, adstock transformations, and stationarity considerations.
• Test different prior distributions to ensure stability, identifiability, and interpretability.
• Support in building automated pipelines to ingest, clean, and update weekly/monthly data and manage refresh automation.

We may use artificial intelligence tools to assist with the screening, assessment, or selection of potential applicants for this position.