Credit Risk Data Analyst (Consumer Lending) 信用風險數據分析師

**About us** Gogolook is a leading TrustTech company founded in 2012 and listed on the Taiwan Stock Exchange in 2025 under the stock code 6902. With "Build for Trust" as its core value, the company has expanded its business from Asia to Europe and America. Gogolook’s AI technology is built on the world's largest database of digital scam data, encompassing phone numbers, websites, virtual currency wallet addresses, and other factors. The company provides diverse anti-scam and fintech services for both consumers and businesses. Its anti-scam offerings include the digital anti-scam app "Whoscall" and a range of enterprise scam prevention solutions in combination with "ScamAdviser." The Fintech BU empowers consumers through data-driven financial services and inclusive lending: （袋鼠金融）offers transparent matchmaking for financial products like credit cards, while JUJI（招財麻吉）provides an innovative microloan service for rapid, convenient funding during urgent financial needs. A foundation member of the Global Anti-Scam Alliance (GASA), Gogolook has also teamed up with a number of institutes such as the Taiwan National Police Agency Criminal Investigation Bureau, the Financial Supervisory Service of South Korea, Thai Royal Police, the Fukuoka city and Shibuya City government, the Philippines Cybercrime Investigation and Coordinating Center, and the Royal Malaysia Police and state government to fight scam, dedicated to creating a "scam-free environment." **Why you should join Gogolook** 1. Influential products: What we make are meaningful products that create values for society and defend against frauds. 2. Emphasize self-growth: We encourage technical community activities, subsidize tickets for conferences and workshops so that learning is continuously supported by the company. 3. Unleash your talent: We respect the professional opinions of everyone, encourage team members to discuss with each other, and make awesome products together. 4. Transparent culture: We publicly share the company's information to all, every member can read and feedback, and become a part of participating in the proposal. ### 職務使命 身為 RSBU 團隊的核心成員，你的任務是從數據的角度出發，協助產品做出以數據為依據的決策。你將專注於數據驅動的分析方法，特別是在 BNPL（先買後付）、小額貸款相關業務中，透過交易行為、還款表現、信用風險等第一方數據，協助產品優化與風險控管。 剛加入時，你會比較貼近數據執行面：獨立完成分析任務、將分析結果主動與團隊夥伴分享、驗證，並且以有效率、即時回應業務需求的方式產出價值。隨著你對業務越來越熟悉，我們期待你能開始主動從模糊的業務痛點（例如「某族群逾期率上升」）自己定義出可驗證的假設，主導比較進階的分析工作（像是額度策略的敏感度分析、風險與轉換率間取捨的策略分析），必要時直接跟高階主管報告關鍵的統計風險。 ### 主要職責 - 假設驗證：將產品或業務問題（如 BNPL、貸款用戶違約風險、還款行為變化）轉化為可驗證的統計假設，並透過數據驅動後續行動 - 資料工程：針對 BNPL 交易與貸款還款數據進行清理、篩選，準備可用於測試與建模的資料集 - 分析與效益評估：評估新數據源（如類聯徵資料、第三方信用數據）對風險模型的邊際貢獻；量化信用政策調整對逾期率、壞帳率、營收等關鍵指標的影響 - 模型建置：參與信用風險模型的開發或驗證，確保產品保有風險區隔力 ### 資格條件 - 統計、資料科學或其他量化相關科系學士學位 - 3–5 年相關領域經驗（依學歷背景可調整） - 需具備貸款、BNPL、消費金融（含信用卡、現金卡、個人信貸）或其他金融科技產品等數據分析經驗 - 高度獨立、自我驅動，能在團隊環境中同時管理多項任務 - 具備從錯誤中學習的能力，持續追求新技能與技術知識的自我成長 - 具備良好的團隊合作精神，理解如何有效率且即時地創造價值 - 主動溝通者，能主動反應資料品質與分析上的風險 ### 技能與能力 - 熟悉 Python（Pandas、Numpy、Scikit-learn） - 熟悉 AWS Athena SQL 及資料分析 - 具備假設檢定、信賴區間等統計能力 - 具備清楚記錄實驗設計、假設前提與最終結果的習慣 - 具備資料集準備經驗，包含訓練與測試資料的清理、篩選 - 熟悉信用風險/違約模型相關指標與分析方法者為佳（如 Vintage 分析、Roll rate、Delinquency 分析） ### 加分條件 - 曾在貸款或 BNPL 相關產品中，實際參與過信用風險評估、額度核定策略或還款行為分析者，可大幅加分 - 熟悉貸款/BNPL 產業常見指標與分析框架，例如： - 逾期率、壞帳率 - Vintage 分析、Roll rate 分析 - 核准率分析與准駁策略的 Trade-off - 客群風險分層（Risk Segmentation）、評分卡（Scorecard）基礎概念 - 曾參與過信用政策（Credit Policy）調整的 A/B 測試或影響評估，例如額度上調/下調、還款期限調整、催收策略優化等實驗設計經驗者尤佳