Job Description

本ポジションは日本語JDの用意がありません。

　
Growth Data Scientist, US App

• Employment Status:　Full-time
• Work Hours: Full Flextime (no core time) 　

• Office: Roppongi

For more details, see the of Our Positions section on our Careers site.

　
About Mercari

Circulate all forms of value to unleash the potential in all people

"What can I do to help society thrive with the finite resources we have?" The Mercari marketplace app was born in 2013 out of this thought by our founder Shintaro Yamada as he traveled the world. We believe that by circulating all forms of value, not just physical things and money, we can create opportunities for anyone to realize their dreams and contribute to society and the people around them. Mercari aims to use technology to connect people all over the world and create a world where anyone can unleash their potential. For more information about Mercari Group’s mission, see Mercari’s Culture Doc

　
Organization/Team Mission

Mercari Engineering Principles

Mercari Engineering Principles are a shared understanding that serves as the foundation of engineering beliefs and behavior at Mercari. The Engineering Principles are designed to complement the organizational identity (Mercari’s mission, values, and culture) from an engineering viewpoint.

These principles ultimately help us achieve Mercari’s mission by defining the ideal state we seek to realize in the long term.

• Passion For The Product
• Grow Together
• Solve Through Mechanisms
• Collaborate Openly

For more details, please see the following link:

• Engineering Culture

This position is for Mercari US

Operating with a high degree of autonomy, this role partners tightly with Growth, Marketing, and Product teams to translate abstract growth opportunities into ML-driven decision frameworks. The Growth Data Scientist prioritizes business impact, thriving in fast experiment-iterate cycles and taking direct accountability for measurable business results.

See here for more information about our mission and values.

　
Work Responsibilities

• Drive ML-Powered Interventions Design, build, and productionize models that predict user behavior (e.g., conversion, churn, and reactivation) to estimate incentive elasticity and incremental business impact.
• Innovate Personalization Systems Architect the shift toward dynamic incentive control, intelligent exposure, and highly personalized targeting at scale.
• Own Business Outcomes Take direct responsibility for marketing and incentive ROI, incremental GMV, and LTV uplift, utilizing model performance as a powerful lever for business success rather than just an end goal.
• End-to-End Experimentation Actively drive the ML lifecycle from experiment design and KPI definition to post-launch analysis and continuous iteration.
• Cross-Functional Partnership Collaborate tightly with Growth, Marketing, and Product teams to translate complex growth opportunities into scalable, ML-driven decision frameworks.
• Build Reusable Growth ML Foundations Develop shared frameworks for uplift modeling, elasticity estimation, and intervention optimization to accelerate the rollout of future growth initiatives.

　
Unique Challenges

• Driving High-Precision Personalization at Scale As our user base grows, the opportunity to optimize incentives and notifications at the individual level is massive. Your challenge will be to build intelligent ML models that deliver the exact right message and incentive to the right user at the optimal time, maximizing incremental ROI and unlocking non-linear business growth.
• Solving Ambiguous Growth Problems Unlike traditional ML roles focused on optimizing existing features, Growth Data Scientist operates in a highly dynamic environment. You will navigate ambiguous problem spaces and balance complex business trade-offs, determining where advanced ML adds the most value to the user journey.
• Optimizing for Business Impact Success in this role isn't solely measured by model accuracy or offline evaluation. It is measured by tangible impact on core business metrics (ROI, GMV, LTV). You will be challenged to thrive in a fast-paced, experiment-driven culture where rapid iteration from prototype to production is prioritized over long development cycles.

　　
Qualifications

• Required Experience/Skills
• Strong interest in growth, marketing, and direct business impact, with a willingness to explicitly own business impact.
• Proven experience applying machine learning to real, user-facing decisions and production environments.
• Proficiency in Python and SQL; experience with ML frameworks (e.g., scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch)
• Experience with large-scale data processing tools (e.g., BigQuery, Spark, or equivalent)
• Solid understanding of statistics, experimental design, and causal reasoning
• Familiarity with ML deployment and monitoring in production systems
• Preferred Experience/Skills
• Prior work experience in a C2C marketplace or in a similar domain.
• Experience with both RDBMS and NoSQL databases, as well as exposure to backend engineering practices (e.g., microservices, Go, gRPC) and cloud platforms, are a plus.
• Language
• Japanese: Preferred
• English: Required

For details about CEFR, see here

　　
Learn More About Mercari Group

• Careers site: https://careers.mercari.com/en/
• Mercan: https://mercan.mercari.com/en/
• Social media: X / Linkedin

　　
Recruiting at Mercari

At Mercari Group, we value empathizing with and embodying the mission and values ​​of the Group and each company. To promote the creation of an organization that maximizes the total amount of value exhibited by all members, we would like to understand the experience and skills of each candidate as accurately as possible.

Recruiting cycle at Mercari Group

• Application screening
• Skill assessment: For engineering positions, you will be asked to complete a skill assessment on HackerRank or GitHub. For non-engineering positions, you may be asked to complete an assessment depending on the position. (The timing of the assessment may coincide with the interview process.)
• Interview: The number of interviews may vary depending on the position.
• Reference check: We will ask for online references around the timing of the final interview.
• Offer: Offers will be determined carefully in consideration of the final interview and the reference check.

　Learn more about our recruiting process here

　
Equal Opportunity Hiring

Here at Mercari, we work to realize a world in which no one’s potential is limited by their background and everyone has the opportunity to freely create value. We also firmly believe that a mindset of Inclusion & Diversity is essential for us to achieve our mission.

This, of course, extends to our hiring practices as well. Mercari is committed to eliminating discrimination based on age, gender, sexual orientation, race, religion, physical disability, and other such factors so that anyone who shares our mission and values can join us, regardless of their background. For more details, please read our I&D statement

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