Data Analyst

Job Description:
Responsibilities:
-Understand the requirement, the global team needs to implement FDP for Japan market based on business requirements.
-Perform fit-gap analysis between global team needs and existing data in Japan, including availability, and acquiring data from primary or secondary data sources.
-Identify the data meanings, unit, calculate logic for each data column the global team needs, and determine the methodology for filling the gap such as developing calculation logic, filling null or ignore, and system interface to be required.
-Develop it with stakeholders and/or 3rd party vendors.
-Clear communications in Japanese and English.
-Works with the relevant stakeholders to explore, design, plan, and implement the required changes for their functions and/or IT services.

Experience:
-Proven working experience as a Data Analyst or Business Data Analyst.
-Technical expertise regarding data models, database design development, data mining, and segmentation techniques.
-Strong knowledge of and experience with databases (DWH, BI, SQL, etc.), and programming (XML, Javascript, or ETL frameworks).
-Strong knowledge of system interface and data architectural design.
-Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.

Required skills:
-Strong analytical skills are fundamental. Should be proficient in data analysis techniques, statistical analysis, and data visualization.
-5 or more years of experience as a Data Analyst or Business Data Analyst.
-5 or more years of experience in managing and leading data analysis projects, including collaborating with cross-functional teams and stakeholders.
-Excellent verbal and written communication skills are crucial both in Japanese and English.
-Proficiency in data analysis tools such as Python, R, SAS, or similar programming languages is essential.
-Proficiency in working with databases, including writing complex SQL queries for data extraction and manipulation.
-Proficiency in working with cloud-based technology such as AWS or Azure.
-Proficiency in system interface and data architectural design.

Nice to have skills:
-Proficiency in data visualization tools like Tableau, Power BI, or Matplotlib/seaborn for creating clear and compelling data visualizations.
-In-depth knowledge of statistical methods and tools for conducting advanced analysis, hypothesis testing, and predictive modeling.
-Familiarity with machine learning algorithms and big data techs such as Hadoop or Spark.
-Expertise in both the retail industry and finance sectors.