Data Analyst

**About the company:** PayPay Card Corporation Chiyoda City, Tokyo PayPay Card was established in 2021 to provide users with more accessible and convenient FinTech services that were previously not possible with credit cards and credit services by integrating with the PayPay payment platform. **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 **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 have:** 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