Marketing Data Scientist

BMO Financial Group; Toronto; On-site; CAD 67,000 - 125,000; Full time

Job summary

A leading financial institution is seeking a Marketing Data Scientist to join their North American Marketing Data Science team. This pivotal role involves advancing in-house marketing analytics capabilities through Marketing Mix Modeling and A/B testing. The ideal candidate will possess strong analytical skills, hands-on experience with open-source tools, and a proficiency in Python and SQL. A competitive salary range of $67,200 to $124,200 is offered, along with various health benefits and a commitment to diversity and inclusion.

Benefits

Health insurance

Tuition reimbursement

Accident and life insurance

Retirement savings plans

Qualifications

• 4–6 years of experience in marketing analytics, data science, or econometrics.
• Strong hands-on experience with open-source MMM tools.
• Solid understanding of MTA, attribution modeling, and design of experimentation.

Responsibilities

• Lead the development and implementation of in-house MMM solutions.
• Provide expert guidance on data management, analytics, and visualization technologies.
• Build and maintain relationships with internal and external stakeholders.

Skills

Data-driven mindset

Strong analytical skills

Excellent communication skills

Education

Post-secondary degree in Statistics, Economics, Data Science, Computer Science, or Marketing Analytics

Tools

Robyn

LightweightMMM

PyMC

Python

SQL

PowerBI

Job description

Application Deadline: 01/09/2026

Address: 33 Dundas Street West

Job Family Group: Data Analytics & Reporting

We are seeking a highly skilled and inquisitive Marketing Data Scientist to join our North American Marketing Data Science team. This role will be pivotal in advancing our 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, causal inference, and A/B testing frameworks, and will be passionate about translating complex data into actionable insights that drive smarter media investment, customer engagement, and marketing optimization.

Key Responsibilities

• Consult 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.
• Lead the development and implementation of in‑house MMM solutions using open‑source packages (e.g., Robyn, Meridian, LightweightMMM, PyMC).
• Design, develop, and implement innovative analytical solutions including MMM, MTA, and causal inference frameworks.
• Design and execute robust experimentation frameworks including A/B testing, uplift modeling, and causal inference to evaluate marketing effectiveness.
• Provide expert guidance on the configuration, functionality, and usability of data management, analytics, and visualization technologies.
• Support the development of strategy and roadmap for data quality, modeling, reporting, and advanced decision‑support tools and develop scalable, reproducible analytical pipelines for marketing analytics.
• Build and maintain effective relationships with internal and external stakeholders to align analytics with business goals.
• Structure and assemble multi‑dimensional data sets across various granularities (e.g., customer, product, transaction, media).
• Integrate data from multiple sources to enhance analysis, streamline reporting, and improve marketing performance measurement.
• Document and maintain operational procedures related to analytical and reporting processes.

Education & Experience

• Typically, 4–6 years of experience in marketing analytics, data science, or econometrics, with a post‑secondary degree in a quantitative field (e.g., Statistics, Economics, Data Science, Computer Science, Marketing Analytics).

Technical Skills

• Strong hands‑on experience with open‑source MMM tools (e.g., Robyn, LightweightMMM, PyMC, Prophet).
• Proficiency in Python and SQL; familiarity with R is a plus.
• Solid understanding of MTA, attribution modeling, causal inference, design of experimentation.
• Experience with cloud‑based data platforms (e.g., AWS, GCP, DataIku).
• Skilled in data visualization tools (e.g., PowerBI, Looker, Tableau).

Core Competencies

• Strong analytical and problem‑solving skills with a data‑driven mindset.
• Excellent communication skills with the ability to influence and collaborate across teams.
• Ability to work independently on complex analytical tasks and deliver high‑impact insights.

Nice to Have

• Familiarity with traditional and digital media data sources (e.g., Kantar, Nielsen, Google Ads, Meta).
• Experience building custom MMM models from scratch and validating them through experimentation.
• Knowledge of Bayesian modeling and probabilistic programming.

Salary: $67,200.00 - $124,200.00

Pay Type: Salaried

BMO Financial Group’s total compensation package will vary based on location, skills, experience, education, and qualifications for the role, and may include a commission structure.

BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans.

About Us

At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.

As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one – for yourself and our customers. We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in‑depth training and coaching, to manager support and network‑building opportunities, we’ll help you gain valuable experience, and broaden your skillset.

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other’s differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.