Marketing Analyst

Job Description:

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.

Job Summary:

We are looking for a results-driven Data Analyst who can transform complex data into clear, actionable insights that support strategic and operational business decisions. The ideal candidate brings strong analytical thinking, hands-on experience with SQL and Python, and the ability to communicate findings clearly to both technical and non-technical stakeholders. You thrive in ambiguous environments, 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.

Key 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.

Minimum Requirements:

• 2–5 years of experience in data analytics, data science, or a related role

• Advanced SQL proficiency (complex joins, window functions, performance optimization)

• Strong Python skills for data analysis and data science (pandas, numpy, scikit-learn)

• 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.

Preferred Qualifications:

• 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

• 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

• Experience building more scalable, automated, and AI-enabled analytics workflows.

#LI-EP1

Five Principles for Success
Our worldwide practices describe specific behaviors that make Rakuten unique and united across the world. We expect Rakuten employees to model these 5 Shugi Principles of Success.

Always improve, Always Advance - Only be satisfied with complete success - Kaizen
Passionately Professional - Take an uncompromising approach to your work and be determined to be the best
Hypothesize - Practice - Validate – Shikumika - Use the Rakuten Cycle to succeed in unknown territory
Maximize Customer Satisfaction - The greatest satisfaction for our teams is seeing their customers smile
Speed!! Speed!! Speed!! - Always be conscious of time - take charge, set clear goals, and engage your team

Rakuten is an equal opportunity employer. Accessibility accommodations for candidates with disabilities participating in the selection process are available on request. Any information received related to accommodation needs of applicants will be addressed confidentially. 

Rakuten would like to thank all applicants for their interest in this role however only qualified candidates will be shortlisted.

Beware of fraudulent job offers claiming to be from Rakuten. Rakuten does not send unsolicited job offers or request money during the recruitment process. Learn more: https://rakutenemploymentalert.com/

At the time of posting, Rakuten expects the Compensation (base salary + discretionary bonus) for this role to be within the range shown below. Individual compensation will vary based on job-related factors, including the skills, qualifications, and experience of the successful candidate as well as business need and geographic location. The successful applicant for this role will be eligible for stock options, health, vision, dental insurance, RRSP matching, Personal Time Off (PTO), Volunteer Time Off (VTO), and other employee benefits as the company implements.