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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

【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

Manage the process for collecting, analyzing, and interpreting people data and turn data into insights. Conduct reports with specific analytic initiatives to articulate internal people questions and support HR strategy, operations, and projects. As a partner to empower BPs to analyze and interpret people data independently. Continuously search for new data sources relevant to advanced analytics models of the people in TSMC for business purposes. Continuously improve the efficiency and effectiven

#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

Get data from both internal and external sources via API or crawlers. Perform data analysis to help marketing/business teams to answer business/operational questions. Build and optimize models for business decision making. Interpret trends or patterns from complex data sets by using statistical and visualization tools. Conduct data analysis reports to illustrate/visualize the results and insight. Build analytics tools that utilize the data pipeline to provide insights to customer needs

我們是巧克科技新媒體，負責LINE TV營運，資料團隊致力於研究平台用戶行為，你將經手千萬筆數據來解決層出不窮的商業問題，有時會與創意無限的行銷團隊配合，藉由數據優化導流成效，並協助

Responsibilities ● Carrying out keyword research using software such as aHrefs, SEMrush, and Google Keyword Planner to optimize web content ● Tracking website performance and generating insights/optimization plans such as organic traffic, conversion rates, and time spent on the page using platforms such as Google Analytics and Similarweb ● Monitoring and reporting on search trends and SEO performance using Google Trends ● Performing competitor analysis to identify content gaps and areas for impr