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蚂蚁金服蚂蚁国际-风险策略专家-国际事业群

社招全职5年以上风险管理-风险策略运营地点:杭州 | 深圳状态:招聘

任职要求


1. 本科及以上学历,数学、机器学习、统计、人工智能、模式识别、计量经济学、计算机等相关专业,硕士优先
2. 精通数据挖掘和风险建模等技术,熟悉常用的数据算法和建模工具,有前沿机器学习算法经验的优先
3. 优秀的逻辑思维能力,高度的业务敏感性与数据敏感性,能够适应高强度、快节奏的工作氛围
4. 良好的学习意愿和学习能力,能够快速掌握工作所需技能
5. 曾在银行、小贷公司、互联网等行业从事过量化风险管理和数据模型工作,有小微风险管理经验者优先
6. 5年以上风控算法、风控数据分析、量化风控策略工作经验

1. Bachelor's degree or above, majoring in mathematics, machine learning, statistics, artificial intelligence, pattern recognition, econometrics, computer science, etc., master's degree preferred
2. Proficient in data mining and risk modeling technologies, familiar with common data algorithms and modeling tools, those with experience in advanced machine learning algorithms are preferred
3. Excellent logical thinking ability, high business sensitivity and data sensitivity, able to adapt to high-intensity, fast-paced work atmosphere
4. Good willingness and ability to learn, able to quickly master the skills needed for work
5. Experience in quantitative risk management and data modeling in banks, small loan companies, internet industries, etc., those with experience in micro-risk management are preferred
6. More than 5 years of experience in risk algorithm, risk analysis, and quantitative risk strategy

工作职责


1. 深入了解信贷产品的产品属性、业务场景、客群特征、风险模式,制定与业务模式匹配的风险管理流程和政策框架
2. 结合银行内外部数据,对体系内外的存量及潜在客户的信用风险和欺诈风险进行评估与计量
3. 负责贷前、贷中、贷后的风控模型、规则、策略等相关风控体系的制定、优化、监控,并和其它风险部门形成联动
4. 基于量化风控能力对不同客群的准入门槛、授信额度、价格及对应还款方式进行差异化,使之实现既定目标最优化
5. 将数据挖掘成果转化成政策优化方案并部署在决策系统,同时负责协调技术、数据和模型团队将风险策略实施上线
6. 跟踪市场、行业、舆情情况,为业务发展和风险管理规划提供数据支持和决策依据,驱动风险管理体系的持续优化

1. Deeply understand the product attributes, business scenarios, customer characteristics, and risk patterns of credit products, and develop risk management processes and policy frameworks that match the business model
2. Evaluate and measure the credit and fraud risks of existing and potential customers within and outside the system using internal and external bank data
3. Be responsible for formulating, optimizing, and monitoring risk control models, rules, strategies, and related risk control systems before, during, and after lending, and coordinate with other risk departments
4. Differentiate access thresholds, credit limits, pricing, and repayment methods for different customer groups based on quantitative risk control capabilities to achieve optimal goals
5. Convert data mining results into policy optimization plans and deploy them in decision-making systems, while coordinating with technical, data, and modeling teams to implement risk strategies online
6. Track market, industry, and public opinion trends to provide data support and decision-making basis for business development and risk management planning, driving continuous optimization of the risk management system
包括英文材料
学历+
机器学习+
模式识别+
数据挖掘+
算法+
数据分析+
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