Senior Analyst, Media Effectiveness

dentsu•Toronto, ON

1d•CA$75,000 - CA$80,000•Onsite

About The Position

We are Dentsu. We innovate in the way brands are built. That means we do things differently to make them better than they were before. In this way, we ensure that our clients' most important marketing assets - their brands - win in a changing world. Dentsu innovates the way brands are built for its clients through its world-class expertise and capabilities in media, customer relationship management and creative communications services. Headquartered in London, Dentsu operates in 145 countries around the world with more than 50,000 dedicated specialists. The Senior Analyst, will be part of a cross-functional team, specifically focused on developing mixed marketing models for our clients. The ideal candidate is a proactive self-starter and is well versed in the data modeling process: whether it’s data collection, data tidying, statistical modeling, and communicating insights to non-technical teams.

Requirements

Proficient in SQL, Python, and/or R for data manipulation, statistical modeling, and automation.
Strong knowledge of statistical methods, including regression analysis, Bayesian modeling, time-series forecasting, and causal inference techniques.
Experience with data visualization tools such as Tableau, Power BI, or Python libraries (Plotly, Seaborn, Matplotlib) to create clear, impactful dashboards and reports.
Familiarity with cloud platforms like AWS, Google Cloud (BigQuery), or Azure for large-scale data processing.
Understanding of marketing channels (TV, digital, search, social, OOH) and how they influence business outcomes.
Strong problem-solving skills with the ability to approach complex business challenges analytically and strategically.
Excellent communication and presentation skills, with the ability to convey technical findings to non-technical audiences.
Experience in project management, with the ability to manage timelines, deliverables, and stakeholder expectations effectively.

Nice To Haves

Experience with open-source MMM frameworks and advanced machine learning techniques.
Knowledge of marketing attribution models, budget allocation strategies, and optimization techniques.
Background in experiment design, including A/B testing and geo-lift studies for marketing campaigns.

Responsibilities

Collaborate with the project lead to understand client objectives and design robust statistical and econometric attribution models.
Develop, validate, and refine statistical and econometric models, including Marketing Mix Models, to measure marketing effectiveness across channels.
Build statistical analyses aligned with business needs, focusing on ROI, marginal returns, and budget optimization.
Utilize open-source MMM tools such as Google Meridian, Meta Robyn, and Light-weight MMM, while exploring custom modeling approaches when necessary.
Explore and implement a variety of statistical and analytical techniques, including linear and non-linear regression, Bayesian time-series forecasting, hierarchical models, and machine learning algorithms (e.g., random forests, gradient boosting).
Prepare and manage structured and unstructured data sources, ensuring data quality through effective ETL processes and rigorous validation checks.
Automate data pipelines and model workflows using tools like SQL, Python, dbt, or Airflow to improve efficiency and scalability.
Conduct scenario simulations, what-if analyses, and incrementality tests (e.g., geo-lift, A/B testing) to validate model outputs and improve attribution accuracy.
Work closely with the project lead to translate complex analytical outputs into actionable insights and strategic recommendations for clients and industry stakeholders.
Interpret model results within the context of the client’s business and industry to identify relevant trends, growth opportunities, and actionable strategies.
Communicate technical concepts effectively to both technical and non-technical stakeholders through clear storytelling, visualizations, and presentations.