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Application of statistics, Machine Learning, Data Mining, pattern recognition and other data analysis techniques to collect, explore, and extract insights from very large scale structured and unstructured data and summarize the results by data visualization tools to support fab operations.

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

工作職責： 負責推薦系統和廣告變現相關的數據支持，包括但不限於數據報表平台、數據分析平台等 負責數據的自動化分析處理工作，對巨量數據進行挖掘，產出數據分布規律、變化趨勢、關聯關系

【Game changer, armed with data.】 You know all about our users, through data analysis. And because you do, you can identify issues and present insights to our Product Owners, spurring them into action. Working with your team, you play a key role in enhancing our business value. After all, you're the one who ignited the spark. And no spark, no fire. 【What a Data Analyst does in Titansoft】 ．Use Google Analytics data

Produce marketing KPI dashboards and deliver daily-weekly-monthly cross-channel performance reports with actionable insights Come up with conversion optimization strategies with the aim of improving efficiency in digital marketing and increasing ROI Implement tracking into various marketing initiatives using Google Tag Manager or other tools Benchmark performance across all digital channels and advice on KPIs based on performance analysis Analyze end-to-end user behavior, conversion data, custom

上廣深、香港、台灣。 涵蓋零售、醫療、金融、廣告、政府等產業。 工作內容： 協助客戶進行數據處理 (data clean/transform/labeling/profiling/feature selection …etc) 協助客戶數據分析建模 協助客戶將分析結果視覺化 協助客戶搭建Private Data Management Platform

成長、O2O 等各種領域。 1.建立、分析現有客戶資料，並提出數據洞察與行銷建議。 2.透過資料探勘(Data mining)與大數據(Big data)進行客戶行為分析，建立預測模型找出精準客群，提升行銷成效。 3.利用各項

1. 擷取、管理、處理數據。 2. 整理龐雜的巨量資料(各產品結構與非結構資料等)，以洞察商機。

- 收集市場需求、業務分析報告、及可視化的數據分析。 - Gather business requirements for business analytics in the areas of drill-down analysis, dash boarding, reporting, visualization and data mining analysis. - 挑戰公司的客戶和合作夥伴，始終領先一步，確定可以與客戶一起進行哪些改善。 - Coach and challenge