Data Science Analyst

About the Company

The organization is part of a global media and marketing communications group known for building innovative, measurable solutions for clients across a wide range of industries. It operates with a strong emphasis on collaboration, high standards, and the blend of creativity, analytical thinking, and data-led decision-making. The workplace culture is centered on community impact, professional growth, and inclusion, with a focus on diversity, equity, and belonging across its teams.

About the Role

This position is for a Data Science Analyst joining a growing data science function. It is a strong fit for someone with a solid grounding in statistics and analytical methods who wants to work in a fast-moving, client-oriented setting. The role involves supporting the creation, testing, and delivery of quantitative models such as marketing mix models, regression-based analyses, and related statistical work across media, pricing, and promotional data. The insights produced in this role will help shape marketing strategy and business decisions for clients. It is also a practical entry point for someone looking to deepen experience in applied analytics while working with senior colleagues on varied projects across different sectors.

Responsibilities

• Develop and support data science models, including marketing mix models built with regression methods, using weekly or monthly time-series data from media, pricing, and promotional sources.
• Review, clean, and validate client datasets so they are accurate and ready for modeling.
• Carry out statistical work such as adstock calculations, diminishing returns analysis, and decomposition outputs.
• Help document models and prepare deliverables like Excel files, charts, and summary tables for both internal stakeholders and client-facing presentations.
• Work closely with senior team members on methodological choices and model improvements to strengthen accuracy and reliability.
• Assist with internal tools and workflow enhancements that improve team efficiency and scalability.

Requirements

• A bachelor’s or master’s degree in Statistics, Mathematics, Economics, Data Science, or another quantitative discipline.
• Strong understanding of statistical modeling, especially regression analysis and time-series techniques.
• Ability to use Python or R for data preparation, modeling, and visualization, including tools such as pandas, statsmodels, and scikit-learn.
• Knowledge of model diagnostics such as multicollinearity, heteroscedasticity, fit assessment, and variable selection.
• Experience handling large, complex datasets with careful attention to detail.
• Clear written communication skills for describing analytical processes and results.
• Exposure to Bayesian methods or hierarchical modeling is an advantage.
• Familiarity with marketing datasets such as media spend, impressions, GRPs, or consumer data.
• Prior internship or academic project experience in an applied analytics environment.

Perks and Benefits

• Practical exposure to a wide variety of industries and client types.
• A collaborative, learning-oriented environment with guidance from experienced professionals.
• Experience across the full marketing mix modeling process, from data intake through to client delivery.
• Annual compensation in the range of CAD 55,000 to CAD 65,000.
• Paid time off that includes vacation, wellness days, long weekends, and half-day Fridays.
• Flexible hybrid working options based on individual needs.
• Training and development opportunities, including education in mental health and inclusion.
• Access to a global network of agencies and resources.
• Participation in employee communities such as Black Employee Network, Girls on Fire, Hispanic or Latinx Alliance, Neuro Network, Pan-Asian Network, and Rainbow Lounge.

Equal Opportunity

The employer is committed to providing equal employment opportunities and maintaining an inclusive workplace. Hiring and employment decisions are made without discrimination based on race, colour, ethnicity, gender, age, religion, creed, national origin, sexual orientation, gender identity, marital status, citizenship, genetic information, disability, or any other legally protected characteristic.