Marketing Analyst

Rakuten Rewards•Toronto, ON

1d•CA$63,394 - CA$99,112•Onsite

About The Position

Rakuten International is a division of Rakuten Group, Inc., a Japanese global technology leader in services that empower individuals, communities, businesses and society. Headquartered in San Mateo, California with more than 4,000 employees worldwide, the Rakuten International business portfolio includes market leaders in e-commerce, digital marketing, advertising, communications and entertainment. We create products and services that provide exceptional value by aligning members and the businesses that want to engage them in a shared community. Rakuten is a leading shopping platform that offers Cash Back on purchases from your favorite brands. By partnering with thousands of brands in apparel, beauty and wellness, dining, grocery, travel, on-demand services, subscription boxes, and more, Rakuten helps members save and get more on everyday purchases. Since its founding in 1999, Rakuten has become the largest and most rewarding shopping program, and its members have earned $4.6 billion in Cash Back just for shopping through Rakuten. For more information, visit Rakuten.com. We are looking for a results-driven, mid-level Marketing Analyst who can transform complex data into clear, actionable insights that support strategic and operational marketing decisions. The ideal candidate brings strong analytical thinking, hands-on experience with SQL (Python a plus), and a solid understanding of e-commerce and two-sided marketplace business dynamics, along with the ability to communicate findings clearly to both technical and non-technical stakeholders. This role goes beyond surface-level reporting, requiring the ability to identify true root causes and connect business data to broader business problems. You thrive in ambiguous environments-particularly during the first three months of training, when direction will still be taking shape-can move fluidly between business questions and technical execution, and are comfortable using modern AI-assisted tools to improve analytical speed, code quality, and workflow automation.

Requirements

Bachelor’s degree in computer science, Economics, Statistics, or a related field required
2-5 years of non-internship experience in data analytics, data science, or a related role (this is a mid-level position, not entry-level)
Advanced SQL proficiency required from day one (complex joins, window functions, performance optimization)
Solid understanding of statistics, probability, and analytical best practices
Experience with experimentation, hypothesis testing, or causal analysis
Hands-on experience with BI and visualization tools (Tableau, Power BI, ThoughtSpot, etc.)
Proven ability to translate business questions into analytical frameworks and communicate insights clearly
Practical experience using Claude Code or similar AI-assisted coding and analytics tools, with the ability to critically review and validate AI generated output.
Understanding of e-commerce or any two-sided marketplace business dynamics
Comfort operating with ambiguity, especially during the first three months of training, including the ability to analyze data and determine the right direction from limited initial guidance

Nice To Haves

Hands-on experience building and validating machine learning models (regression, classification, clustering, time-series forecasting)
Experience supporting ML workflows- feature engineering, model selection, validation, and performance tracking
Python skills for data analysis and data science (pandas, numpy, scikit-learn) - a secondary but valued skill alongside SQL
Familiarity with deploying or monitoring ML models in production environments
Experience with cloud data warehouses (Snowflake, BigQuery, Redshift)
Background in e-commerce, marketing, product, or growth analytics, particularly retention and engagement analysis
Experience building more scalable, automated, and AI-enabled analytics workflows.
Master's degree in Computer Science, Economics, Statistics, or a related field

Responsibilities

Own and monitor key business and marketing KPIs, tracking performance and conducting deep-dive analyses to identify trends, risks, and growth opportunities
Translate business problems into analytical frameworks and deliver clear, actionable recommendations to technical and non-technical stakeholders
Write efficient, scalable SQL queries to extract, transform, and validate data from multiple sources, ensuring metric accuracy and consistency
Perform exploratory data analysis and statistical modeling using Python to inform strategic and operational decisions
Apply statistical techniques to support experimentation, A/B testing, and causal analysis
Build and maintain dashboards and automated reporting using BI tools (Tableau, Power BI, Looker) and develop scalable, reusable analytical assets
Build, validate, and interpret machine learning models, including segmentation, propensity modeling, forecasting, and predictive scoring
Evaluate and apply AI tools responsibly, ensuring analytical outputs are accurate, explainable, reproducible, and aligned with business context.
Conduct in-depth root cause analysis that goes beyond obvious or surface-level issues, connecting business data to technical and operational context to deliver actionable recommendations
Produce retention and engagement growth analysis reports for marketing leadership, routing findings through the appropriate internal review process before they reach VP stakeholders
Apply working knowledge of e-commerce and two-sided marketplace business dynamics to frame analyses and recommendations in the right business context