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入我們，一起創造更多旅遊的可能性與未來。 【你將會參與的事】 1. 與 KKday 其他團隊合作，設計、開發 dbt (data build tool) code，支持各項業務需求，為公司的業務發展提供資料，設計和建立資料分析報告和資料儀表

Introduction As a Data Scientist at IBM, you will help transform our clients’ data into tangible business value by analyzing information, communicating outcomes and collaborating on product development. Work with Best in Class open source and visual tools, along with the most flexible and scalable deployment options. Whether it’s investigating patient trends or weather patterns, you will work to solve real world problems for the industries transforming how we live. Your Role and Responsibilities

We, at iPASS, leverage transit and e-payment data to drive our business. Being one of few companies powering Taiwan's main transportation, iPASS is uniquely positioned in the market as the cornerstone of the e-payment ecosystem. Your role is crucial in helping the team investigate the data and provide analytical reports to support business decisions. You will also be instrumental in developing a flexible dashboard or API for third parties. Let's stay excited

【Responsibilities】 1. Create and maintain optimal data pipeline architecture, assemble large and complex datasets to meet functional/nonfunctional business requirements. 2. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, redesigning infrastructure for greater scalability, etc. 3. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry l

About the Role You will be Forma’s first marketing operations and analytics subject matter expert. We are looking for a marketing operations champion with an excellent understanding of marketing technologies needed to support the business and marketing analytics and data strategies. We are looking for someone who can offer strategic partnership but also lend tactical support to the rest of marketing, enabling them with the insights necessary to drive effective go-to-market outcomes. This person

At SHOPLINE we are working on very interesting initiatives that would involve using data-mining and machine learning. with the vast amount of data that we currently have and growing exponentially. We will share details during the interview. 【What you'll be doing 】 - Develop, operate, and monitor ETL for data collection, cleansing, processing, storage, and analytics - Responsible for data schema management and db performance tuning - Develop backend APIs and maintain data visualization platform f

Job description: Part of You & Mr Jones, the world's first brandtech group, fifty-five is a data company helping brands collect, analyse and activate their data across paid, earned and owned channels to increase their marketing ROI and improve customer acquisition and retention. Headquartered in Paris with offices in London, Hong Kong, New York and Shanghai, the data company was named by Deloitte as one of the fastest-growing tech firms in Europe, thanks to its unique technology

#About the Team Fazz’s Data Engineering teams are responsible for creating and maintaining the infrastructure that runs the company’s data pipeline, and optimizing the flow and collection of data for the critical business analytics and AI/data-driven solutions. The success of the team relies on the high engineering standard and the adoption of cutting-edge technology that empowers the organization to be agile. Data engineering forms the foundation to ensure that precious data

成工作。我們熱愛新想法與導入新科技，任何idea以及嘗試，我們都很熱意討論。 工作內容： 1. Develop and design data / backend service systems for business related purpose. Develop, operate, and monitor ETL for data collection, cleansing, processing, storage, and analytics Design, build, and maintain APIs, services, and systems. Innovate and implement tools to enhance internal team

The Data Platform team enables our customers to ingest and perform real time analytics on critical security insights and intelligence data stored in our vast Data Lake and empower internal engineering teams to leverage the best datastore technology for their needs. Our Big Data technology stack consists of Kafka, Google PubSub, ClickHouse, Google BigQuery etc. We’re looking for software engineers with a background in distributed systems and are excited about the opportunity to work on large-scal