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▋▍About Us｜關於我們（醫療 X 科技） 用數據驅動決策，將生醫資訊轉化為生命的價值。 在慧康生技（Health2Sync），數據是我們最核心的資產。身為數據團隊的一員，你將有機會處理海量且多樣化的生醫數據（Biomedical Data），並透過機器學習與生成式 AI 技術，將其轉化為對用戶及醫療院所有實質幫助的數據產品。 我們不僅僅是技術的執行者，更是公司重大決策的參與者。在這裡，每一份分析報告都可能改變產品走向，每一條數據管線都在支撐全球百萬用戶的健康。期待對數據科學充滿熱忱的你加入，與我們一起用技術為病患與醫療人員創造更多可能性。 ▋▍Why Join Us｜為什麼加入我們 接觸稀缺的生醫大數據：處理真實世界（Real-World Data）的生理指標與健康數據，在技術深度之外，累積珍貴的醫療科技領域知識（Domain Know-how）。GenAI 與 LLM 實戰舞台：不只是開發傳統模型，你將主導基於大語言模型的應用開發，將最新的 AI 技術落地於數位健康場景。從基礎設施到產品落地：參與 Data Lakehouse 的架構設計與優化，親手建立支撐大規模運算與建模的高效率數據管線。高度影響力的決策參與：團隊推崇透明溝通與共創，你的分析結果與模型表現將直接影響產品的發展策略與商業方向。 ▋▍Role Highlights｜職缺亮點 數據科學的最前線：同時跨足數據工程與 AI 建模，讓你成為市面上最搶手的全方位數據專才。賦予數據生命感：看著你寫出的模型轉化為 App 上的健康建議，實質改善病患生活，這種成就感無可取代。純技術、零官僚：我們在乎的是數據的真實性與解決方案的有效性，提供最透明、最尊重專業的工程環境。接軌國際技術標準：與具備國際視野的團隊共事，使用最先進的數據架構處理跨國市場的挑戰。 ▋▍Responsibility｜主要職責 [ 數據基礎設施建構 ] 架構建立與維護：設計並持續優化數據基礎設施（Data Pipeline, Data Lakehouse），以支援高效的數據分析與機器學習建模。管線自動化：使用 Airflow/Dagster 構建穩定、可擴展的 Data Pipeline，並管理大數據儲存架構（如 Apache Iceberg）。 [ AI 與機器學習應用開發 ] 模型開發與部署：利用數位健康數據開發並部署機器學習、統計模型及生成式 AI (GenAI) 應用。LLM 應用實踐：針對產品需求，構建並維護基於大語言模型 (LLM) 的應用服務，提升產品智能化程度。系統性能優化：優化現有的 AI 系統與演算法，確保其在生產環境中的性能與可擴展性。 [ 數據決策支援 ] 跨團隊任務執行：運用分析工具與統計方法，支援產品與業務團隊的特定任務，將數據轉化為可執行的行動建議。數據專案推動：參與數據產品發想，持續探索能優化 H2 產品體驗的數據科學方案。 ▋▍Media Coverage｜媒體報導 《環球生技月刊》慧康生技明掛牌興櫃 《今周刊》打造智抗糖 App 攻入慢性病平台 《數位時代》台灣新創進軍韓國 《今周刊》慧康創業背景 《天下雜誌》台灣第一數位療法

● 建立與維護 ETL / ELT 資料處理流程 ● 建置 Streaming Data Pipeline，處理高併發事件流與日誌資料 ● 維護 Kafka 與即時資料處理架構 ● 規劃與維護 Data Warehouse / Data Mart 資料模型 ● 負責資料清洗、資料驗證與資料品質監控 ● 協助建立可重複使用的中介資料表與分析資料集 ● 優化資料查詢效能與數據處理流程 ● 與產品、營運與工程團隊合作，支援即時 BI 與數據決策需求

為什麼大家喜歡在 RichWell Co.Ltd. 上班？ 1.彈性上班-早上不趕打卡，想多睡一點、避開通勤人潮都OK。2.特休多多-不用等滿一年就能休假，我們比法規更大方，放假就是要爽爽的。3.獎金福利讚 年終、績效獎金該有的都有，努力絕對不白費。4.生日小驚喜，公司記得你的每個重要時刻。5.定期聚餐/Team Building 不只是工作夥伴，更是一起成長的戰友，吃吃喝喝感情更緊密。6.技術課、內部分享會，想學什麼我們都支持，讓你持續進化不退化！ Key Responsibilities for Data Analyst: Responsible for gathering data from various sources, including internal databases, user interactions third-party APIs, ensuring data accuracy and integrity.Perform exploratory and statistical analysis to identify trends, patterns, and correlations in large datasets.Create clear, compelling reports and dashboards to communicate insights of the product to stakeholders.Work closely with product and engineering teams to define key performance indicators (KPIs) and track product performance.Provide recommendations to improve software features, user engagement, and operational efficiency based on data findings.Implement processes to ensure data quality, consistency, and security, adhering to company policies and regulations.Conduct custom analyses to support strategic initiatives or respond to business questions.

【 What You'll be Doing 】- Pipeline Implementation: Develop, maintain, and optimize robust ETL and real-time data pipelines to ensure high-quality data collection, processing, and storage.- System Monitoring: Actively monitor data pipeline health and troubleshoot data quality or performance issues to ensure high availability.- Database Management: Assist in designing data schemas and implementing database indexing or partitioning strategies for performance optimization.- API Tooling: Build and support backend APIs and internal data tools to empower SHOPLINE merchants with actionable insights through visualization platforms.- Collaboration: Work closely with Senior Engineers and Product Managers to translate business requirements into technical data solutions.

At SWAG Live's data team, our mission is to democratize data by building a self-service data platform. We aim to empower internal teams to access, interpret, and derive valuable insights from data effectively.As a Data Scientist in this role, you will collaborate with a multidisciplinary team of engineers and analysts to tackle diverse challenges using quantitative techniques such as statistical analysis and machine learning. You will work with large, complex event-based datasets, conduct exploratory data analysis (EDA), define requirements, and develop deploy models. We are particularly seeking a data scientist with experience in building customized recommendation models and a strong interest in product-focused machine learning development. Responsibilities Leverage state-of-the-art algorithms to build fully customized recommenders and other growth models.Design, deploy and maintain all components necessary for modeling, including feature engineering, automatic model training tuning and engineering toolchains.Create a comprehensive monitoring framework to evaluate model performance and provide actionable insights to drive business growth, focusing on awareness conversion and transactions.Understand stakeholder business requirements and design end-to-end machine learning/AI solutions that are effective, practical, and robust in addressing business challenges.Collaborate closely with data engineers and backend engineers to develop scalable systems.Communicate efficiently with cross-functional teams, promote the implementation of strategic applications, and drive continuous optimization.

WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform. WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement. Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it. The Role: We are seeking an exceptionally talented data scientist with strong modeling and programming skills to join our team. In this role, you will work closely with data science team and technologists across the firm to develop appropriate features and metrics for data processing. Perform analysis and generate models of financial datasets using machine learning techniques Process, clean and verify the integrity of unstructured data and turn data into valuable insights Develop and create data that seek to predict the movement of financial market Transfer data into internal infrastructure applying variety of algorithmic techniques What You’ll Bring: Have a Master’s degree or higher from a leading university in Computer Science, Electrical Engineering or other related areas Good academic record Familiar with modeling, data structures, algorithms and optimizations Strong knowledge of machine/deep learning algorithms Proficient in programming languages of both C++ and Python Possess good communication and presentation skills in English Ability to work independently and as member of a team Research scientist mindset: deep thinker, creative, strong work ethic, persevering, smart a self-starter Detail oriented and capable of multitasking and delivering in fast-paced work environment As a plus: While not mandatory, a strong interest in financial markets will definitely be beneficial Participant of ACM-ICPC By submitting this application, you acknowledge and consent to terms of the WorldQuant Privacy Policy. The privacy policy offers an explanation of how and why your data will be collected, how it will be used and disclosed, how it will be retained and secured, and what legal rights are associated with that data (including the rights of access, correction, and deletion). The policy also describes legal and contractual limitations on these rights. The specific rights and obligations of individuals living and working in different areas may vary by jurisdiction. Copyright © 2025 WorldQuant, LLC. All Rights Reserved.WorldQuant is an equal opportunity employer and does not discriminate in hiring on the basis of race, color, creed, religion, sex, sexual orientation or preference, age, marital status, citizenship, national origin, disability, military status, genetic predisposition or carrier status, or any other protected characteristic as established by applicable law.

【工作職責】 您將加入我們的核心開發團隊，負責銜接後端數據與前端呈現。這是一個結合 Web 開發與數據處理的角色，重點在於將複雜的資料轉化為具價值的視覺化資訊。 數據中台開發：負責中介層 (Middle-tier) 的設計與實作，將後端原始數據進行清洗與轉換 (Data Wrangling)，以供前端介面使用。API 服務建置：開發高效能的 Backend API Server，並實作數據追蹤 (Web-tracking) 與資料蒐集模組。專案協作：參與中大型專案的開發週期，與前端工程師緊密配合，定義資料介接規格，並定期匯報開發成果。

為什麼大家喜歡在 RichWell Co.Ltd. 上班？ 1.彈性上班-早上不趕打卡，想多睡一點、避開通勤人潮都OK。2.特休多多-不用等滿一年就能休假，我們比法規更大方，放假就是要爽爽的。3.獎金福利讚 年終、績效獎金該有的都有，努力絕對不白費。4.生日小驚喜，公司記得你的每個重要時刻。5.定期聚餐/Team Building 不只是工作夥伴，更是一起成長的戰友，吃吃喝喝感情更緊密。6.技術課、內部分享會，想學什麼我們都支持，讓你持續進化不退化！ Responsibilities • Lead and mentor the data analysis team, providing guidance on methodologies, tools, and best practices. • Define data strategy and analytics roadmap aligned with business and product objectives. • Oversee data collection, integration, and governance across multiple sources, ensuring data accuracy, consistency, and security. • Drive advanced analytics initiatives, including statistical modeling, forecasting, and experimentation (e.g., A/B testing). • Partner with product, engineering, and business teams to define KPIs and build scalable tracking frameworks. • Deliver strategic insights and executive-level reports to support decision-making and business growth. • Identify opportunities to improve product performance, user experience, and operational efficiency through data-driven insights. • Establish and optimize dashboards, reporting systems, and data visualization standards. • Promote a data-driven culture across the organization and enhance data literacy among stakeholders.

在數據應用專案中執行並引導成員完成產品的規劃、安裝建置並促進專案團隊協作協助客戶排查產品問題及提供顧問服務執行並引導成員進行數據科技產品之PoC及技術可行性驗證。

在數據應用專案中執行產品的規劃、安裝建置並促進專案團隊協作協助客戶排查產品問題及提供顧問服務執行數據科技產品之PoC及技術可行性驗證