Marketing Science Analyst

RBC; Toronto; On-site; CAD 80,000 - 100,000; Full time

Job summary

A leading financial services institution in Toronto is seeking a Marketing Science Analyst to enhance their marketing optimization efforts. This role requires combining expertise in marketing with technical analytics to expand measurement capabilities and drive effectiveness. Candidates should possess strong analytical skills, experience with data visualization tools, and a solid understanding of media planning. This position offers competitive compensation and opportunities for professional growth.

Benefits

Comprehensive Total Rewards Program

Competitive compensation

Flexible work/life balance options

Qualifications

• 3-5 years of experience in marketing analytics, preferably in financial services.
• Hands-on experience with data analysis and cloud technologies.
• Strong ability to write complex SQL queries.

Responsibilities

• Partner with Marketing teams to identify analytical opportunities.
• Evaluate new data sources for marketing analytics.
• Collaborate with Data Scientists to define model specifications.

Skills

Marketing/media domain knowledge

Analytical skills

Data visualization with Tableau

SQL proficiency

Stakeholder management

Education

Bachelor's degree in Marketing, Business, Economics, Statistics, or Mathematics

Master's degree (MBA, MS in Marketing Analytics) preferred

Tools

Python (pandas, NumPy, matplotlib)

AWS (S3, Glue)

Git/GitHub

Job description

What is the Opportunity?

The Advanced Data Insights & Integration (ADII) Team of Personal Banking is seeking a passionate and innovative Marketing Science Analyst to join our Marketing Optimization & Planning pillar. This is a role that bridges marketing and business expertise with technical analytics capabilities. You will be responsible for identifying business opportunities, evaluating data sources, defining modeling requirements, and partnering with Data Scientists to expand our marketing measurement capabilities. The ideal candidate combines marketing/media domain knowledge with hands‑on analytical skills to drive innovation in how we measure and optimize marketing effectiveness.

What will you do?

• Partner with Marketing and Media teams to translate business challenges into structured analytical problems, identifying opportunities to expand measurement capabilities (e.g., controlled experimentation design, upper vs. lower funnel effect, portfolio‑level product marketing analysis, geographic modeling)
• Investigate and evaluate new data sources for marketing mix modeling and other analytics use cases, such as media execution and attribution metrics, third‑party competitive and market research, internal CRM, web analytics, and transaction data
• Assess data quality, completeness, and granularity of new data sources; determine which metrics should be incorporated into models and why (e.g., impressions for reach‑based analysis)
• Collaborate with Data Scientists to define model specifications, variable selection, and transformation logic, and recommend new modeling capabilities such as geographic models, impression‑based models, and channel interaction effects
• Design and analyze marketing experiments (geo tests, holdout tests) to validate model recommendations and measure incrementality
• Validate model inputs and outputs from a business perspective; conduct deep‑dive analyses to explain model findings and identify drivers of KPI changes
• Create visualizations and dashboards using Tableau, or Python/R libraries
• Serve as liaison between Marketing/Media teams and Data Science team; translate technical model outputs into actionable marketing recommendations and present insights to cross‑functional audiences
• Train marketing teams on interpreting MMM results and using optimization tools; create documentation and manage relationships with external media agencies and data vendors

What do you need to succeed?

Must-have

• Bachelor's degree in Marketing, Business, Economics, Statistics, Mathematics, or related field; Master’s degree (MBA, MS in Marketing Analytics) preferred
• 3‑5 years of experience in marketing analytics, media planning, digital marketing, or marketing strategy roles, preferably in financial services
• Strong understanding of media planning and buying across traditional (TV, radio, print, OOH) and digital channels (display, video, social, search, programmatic); knowledge of media metrics (impressions, reach, GRPs, CPM, CPA, ROAS)
• Python proficiency: hands‑on experience with pandas, NumPy, matplotlib/seaborn for data analysis and visualization
• SQL foundation: strong ability to write complex queries including joins, aggregations, and CTEs
• Experience working with AWS (S3, Glue) or other cloud platforms; comfortable with cloud‑based notebook environments (Jupyter, SageMaker)
• Hands‑on experience analyzing media agency data and reconciling discrepancies; familiarity with marketing analytics platforms (Google Analytics, Adobe Analytics, Google/Meta Ads Manager)
• Understanding of data quality concepts, validation techniques, and ETL/ELT processes; experience with Git/GitHub for version control
• Strong business acumen with ability to connect analytics to business outcomes; excellent communication skills to explain complex concepts to non‑technical audiences
• Stakeholder management experience working with cross‑functional teams (Marketing, Data, Finance, Agencies); problem‑solving mindset comfortable with ambiguity; self‑starter who proactively identifies opportunities

Nice to have

• Experience with marketing mix modeling tools (Meta Robyn, Google Meridian) or exposure to MMM projects; understanding of causal inference concepts (incrementality, test‑and‑learn)
• R programming experience with tidyverse, dplyr, ggplot2
• Advanced data visualization skills with Tableau, Power BI, Looker; ability to build executive‑level dashboards
• Familiarity with programmatic advertising and DSP platforms (e.g., DV360, Amazon DSP)
• Experience conducting geo‑experiments, matched market tests, or A/B testing programs
• Understanding of customer lifetime value (CLV) modeling and attribution models (multi‑touch, data‑driven)
• Experience working in agile/scrum methodologies or contributing to open‑source analytics projects

What’s in it for you?

• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable
• Leaders who support your development through coaching and managing opportunities
• Ability to make a difference and lasting impact
• A world‑class training program in financial services
• Flexible work/life balance options

Application Deadline: 2025‑12‑31

Inclusion and Equal Opportunity Employment

At RBC, we believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.