Top Data Science Jobs in Tokyo
As a Data Scientist for User Acquisition, you will analyze complex datasets to identify growth opportunities for Monster Hunter Now. Your role involves enhancing ETL pipelines, collaborating with teams, developing LTV models, and presenting insights to executives. Staying current with industry trends and effectively communicating data narratives are also key responsibilities.
The Data Scientist will perform statistical analyses on vehicle data, analyze AD/ADAS functionality, and build machine learning tools and data pipelines for efficient data retrieval. They will collaborate with various teams to drive continuous improvement of the data platform.
The Senior Principal Engineer will lead data engineering initiatives, responsible for end-to-end ownership of ETL data pipelines, collaborating across global teams to optimize sales and operational efficiency through data products and insights.
Collaborate with analysis and development teams on data modelling activities, contribute to data application projects, possess expertise in data warehousing and big data technologies, and demonstrate strong communication skills.
As a Data Scientist at Niantic, you will analyze large datasets to provide insights for game performance and user experience enhancement. Responsibilities include developing statistical models, collaborating with cross-functional teams, and creating visualizations to communicate findings and recommendations.
The Analyst Programmer - ETL is responsible for developing and unit testing ETL scripts in IDMC based on design specifications. They will maintain ETL processes, collaborate with teams on data requirements, implement transformations, troubleshoot issues, and document processes while staying updated on ETL development trends.
The Data Engineer II role at Cencora focuses on providing accurate data support for Legal and Compliance departments. Responsibilities include data extraction and analysis, data quality validation, and developing analytics models to address business challenges. The position requires data monitoring, collaborating with teams, and ensuring data integrity for effective decision-making.
The Senior Data Engineer will enhance data processing and analytics pipelines, focusing on scalability, reliability, and business insights. Responsibilities include automating cloud services, developing CI/CD pipelines, and collaborating with stakeholders for analytical needs and product metrics.
The Senior Data Engineer will build scalable data infrastructure, clean and preprocess data for machine learning models, manage large-scale unstructured data, and collaborate with teams to meet data requirements while ensuring data quality.
The Principal Data Engineer will guide the technical planning and development of critical sales tools and business workflows, focusing on data analysis for decision-making. Responsibilities include managing ETL data pipelines, leading the design and implementation of data products, mentoring engineers, and improving data engineering practices while collaborating with various stakeholders.
The Senior Data Engineer will maintain and develop data pipelines for various processes, optimize workflows, and build data quality mechanisms. Collaboration with data analysts and stakeholders is key to crafting innovative data solutions and ensuring compliance with industry best practices.
The Team Lead, Analytics Engineering will oversee a group of engineers, mentor them, and ensure the delivery of high-quality data products. The role involves collaborating with Data Leadership and stakeholders to define and prioritize the roadmap, while also contributing to engineering solutions and managing team dynamics effectively.
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