Data analysis is an indispensable and crucial position for our growth. We strive to enhance our services by leveraging the insights gained from the vast amounts of data accumulated daily. We are moving beyond standard analytics and are heavily investing in statistical modeling, machine learning, and generative AI to predict user behavior, automate our processes, and provide a convenient and secure payment experience for our users.
What Makes This Role Unique
Based on our internal direction, we’re not just looking for an analyst to run queries. We’re looking for a builder who wants to:
- Work with Massive, Complex Data: You won’t be data-starved. You will have access to one of the richest FinTech datasets in Japan, spanning the entire PayPay ecosystem.
- Build the Foundation, Not Just Maintain It: We are in a high-growth phase of transforming our processes. You will help build the data-driven culture you’ve always wanted to work in.
- Solve High-Stakes Product Challenges: Your models and analyses will directly influence our most critical projects.
Responsibilities
- Partner with Product Managers and stakeholders to define key metrics, shape product strategy, and identify new opportunities for growth using advanced data analysis.
- Develop, deploy, and maintain statistical models and ML algorithms (e.g., Python/R) for clustering, segmentation, and predictive analytics to uncover deep insights into user behavior.
- Measure the causal impact of launched projects, distinguishing correlation from causation to understand what truly drives user behavior.
- Help product managers and business leaders formulate and test hypotheses through data analysis and experimentation (e.g., A/B testing).
- Proactively identify insights and opportunities from data, translating complex modeling results into a clear business narrative and actionable recommendations.
- Partner with engineering and product teams on leveraging Generative AI to solve core user problems, including analyzing unstructured data from customer support.
- Build views, tables, and data models on Bigquery using SQL to organize and transform datasets for analysis and feature engineering.
- Maintain and automate key dashboards (Looker Studio) for business metrics and communicate insights to stakeholders on a regular basis.
Requirements
- Strong proficiency in Python or R and associated data science libraries (e.g., Pandas, scikit-learn, statsmodels, Tidyverse).
- Proven experience in applying statistical modeling and ML techniques (e.g., logistic regression, clustering, classification, predictive analytics) to real-world business problems.
- At least 3 years of analytical experience with advanced SQL.
- Experience in designing, executing, and analyzing A/B tests or other controlled experiments.
- Deep understanding of key statistical concepts (e.g., statistical significance, confidence intervals).
- Ability to translate complex data findings into a clear business narrative and actionable recommendations for stakeholders.
- English language in message communication (>= Communication Level English)
- Business level of Japanese language in communication (>= JLPT N1)
Nice to haves
While not specifically required, tell us if you have any of the following.
- Experience with Natural Language Processing (NLP), LLMs, or analyzing unstructured text data (e.g., customer support logs).
- Deep curiosity about the “why” behind data and a strong interest in the FinTech/payments industry.
- Track record of working in a very fast paced environment or a startup
- Worked with a Product Manager to propose business/product recommendations
- Experience in building data warehouses/data marts
- Ownership, willingness to work hard, and fearlessness to move forward
- Experience promoting a data-driven culture within a company
