找工作

1. 金融商品/結構型商品模型建置及驗證。 2. 金融商品/結構型商品模型參數設定及風險敏感度分析。 3. 定期檢視現有模型的適用性及表現，參與新模型適用之評估。 4. 交易評價系統維護及系統驗證。 5.新金融產品模型開發、專案參與及規劃。 關鍵績效指標： 1. 金融商品/評價驗證報告產出。 2. 金融商品/結構型商品模型驗證及開發。 3. 交易系統建置、維護及驗證。 4. 前中後台專案參與。

• Partner with Franchise, Customer Management team and also Product Team to formulate business strategies and using data insights to drive Treasures Acquisition, Engagement and Transaction • Develop and maintain Control Tower, utilize Data Driven Operation Model (DDOM) to maximize value from data and drive strategies deliver business outcomes. • Create visualizations and present clear, concise, and actionable insights to the key stakeholders, lead discussions on analytics and interpretation of results • Develop models and data insights to plan and drive the customer interactions

▌工作說明： 1.風險管理資料分析、報告、監控及風險數值監控。 2.風險資料庫的維護。 3.資產品質檢視分析及改善因應。 ▌具備條件： • 須擅長使用EXCEL進行資料分析與儀表板功能。 • 具其他BI工具運用專長，或資料庫規劃專案執行等經驗為佳。

1.市場風險管理系統架構及管理流程之持續檢視/強化 2.各項外部規範限額控管系統平台規劃及後續建置管理: 配合相關規範要求所建置控管平台。 3.規劃新種金融商品管控流程: 針對交易限額、交易評價、交易系統及監控管理報表、資本計提等，參與前中後台新產品專案討論。 4.規劃建置市場風險資料庫:建置支持數位化、自動化、整合化市場風險的資料庫。

1.通路BU及商品財務績效分析 2.業務獎勵專案Payout合理性 3.檢視業務單位年度預算編列 4.同業財報及法說資訊彙整

1.根據圖面計算工程量、出估價單 2.與 PM 討論成本 3.建立報價資料庫 4.協助老闆審核報價

1.市場風險管理制度、規章之制修訂 2.金融商品的風險辨識與對應管控措施的規劃設計 3.針對風險議題提出建議方案 4.規劃與執行市場風險壓力測試 5.市場風險資本計提(FRTB)之計算

1. IFRS 17專案 2. 精算查核 3. 風險管理

＜About the job＞： The Data Science & AI team of headquarter IT is developing the frontier and practical analytic technologies that enhance the data value. As the data scientist, you‘ll join the AI/Big Data Analytics program/projects related to management topics, including Commercial/Industrial Engineering/Supply Chain/Financial Performance/Operation...etc., to build the model or algorithm to empower data-driven & analytics-driven for driving business value from data insights in this world-class company (Fortune Global 500, 22nd). ＜Job Description＞： •Design, implement and refine advanced Statistical Modeling/Algorithm Models •Ensure alignment of modeling initiatives with the requirement goal defined by key stakeholders and company objectives and identify new hypotheses for model improvements. •Executing big data analysis and predictive analytics projects include feature engineering, model building, algorithm development, etc. •Collaborate effectively with team members, whether leading tasks or supporting initiatives led by others. •Self-motivated, Result-oriented, and interested in applying quantitative methods to solving business and engineering problems. •Able to use the cutting-edge technologies to solve the practical problems ＜Skills＞ •Experience with any one of Machine Learning, Statistical Modeling, Deep Learning, Econometric Modeling, Optimization Algorithm(OR), Numerical Simulation..., etc., model/algorithm building of the practical application in the industry. •Familiarity with programming languages like Python or R, or Java. (Good programming skills in Python is a plus). •Advanced ability to perform Exploratory Data Analysis and working knowledge of statistics. •Ability to visualize data in the most effective way possible for a given task, especially visualize models and results and debug and troubleshoot code and models. •Experience in setting up supervised & unsupervised learning models including data cleaning, data analytics, feature creation, model selection, performance metrics & visualization

1.信用風險模型建置 2.內部評等辦法維護與評等系統需求處理 3.各項風險衡量業務之方法論研發及精進