蔚来活动运营-SH

负责搭建和优化 SHEIN 平台账号风控策略与算法模型，包括但不限于账号安全、反作弊、欺诈检测、团伙挖掘等领域；利用机器学习、深度学习及相关数据分析技术，对用户行为和交易数据进行实时监控与分析，识别可疑行为和潜在风险；与业务、产品和风控团队紧密合作，定义并完善风控指标体系，持续跟进风险案例并制定对应策略；设计并实现高效、稳定的风控数据处理流程，包括数据清洗、特征工程、模型训练及线上预测部署；持续跟踪电商行业风险趋势及新技术发展，及时更新和升级风控算法与策略，提升整体防控能力。

1、市场战略与拓展 * 制定欧美/东南亚/中东等目标市场的跨境电商销售策略，覆盖Amazon、eBay、Shopee等主流平台及独立站 * 分析海外投影行业趋势，挖掘新兴市场机会，建立本地化渠道合作伙伴关系 * 主导海外品牌营销活动，联动市场部制定本土化推广方案 2、团队搭建与管理 * 从0到1组建并培养跨境电商销售团队，搭建人才梯队及绩效考核体系 * 带领团队达成年度销售目标，管理关键客户谈判与大订单落地 3、运营与风控 * 优化跨境供应链流程（物流、清关、售后），提升订单转化率与客户满意度 * 监控国际汇率、关税政策变化，制定风险应对预案

1. 商业化增长战略与规划 制定并落地商业化增长战略，覆盖不同平台广告类型的变现模式，确保收入规模和ROI持续增长。 设计长期商业化路径，优化定价、用户分层、营销激励等，推动业务可持续增长。 关注行业动态和竞品策略，探索新的商业化模式和增长机会。结合市场环境，优化定价、激励机制，提升广告产品offer竞争力。 2. 运营体系搭建与优化 优化商业化运营体系，包括广告主教育、投放策略、漏斗优化策略等. 建立标准化流程和运营机制，实现商业化产品的自动化、智能化运营。 规划并执行推广活动，推动广告主/商家入驻并提升付费意愿。 设计营销工具、活动方案，如折扣、返利、激励等，提升广告投放量和商家参与度。 3. 数据驱动增长与商业决策 优化数据指标体系，深度分析用户/商家行为，驱动商业化策略迭代。 设计数据工具和分析框架，提升收入预测、市场细分、精准营销等能力。 通过A/B测试和实验设计，提升广告主和商家的投放效率和LTV。 结合财务模型（如ARPU、LTV ,ROI等），制定商业优化方案，实现收入最大化。 4. 高效跨部门协作与团队管理 协同产品、技术、市场、销售团队，共同推进商业化目标落地。 推动商业化产品的技术开发与创新 -------------------------------------------------------- 1. Monetization Growth Strategy & Planning - Develop and implement a monetization growth strategy, covering monetization models across various advertising platforms to ensure sustainable revenue growth and ROI improvement. - Design a long-term monetization roadmap, optimizing pricing, user segmentation, and incentive mechanisms to drive sustainable business expansion. - Stay updated on industry trends and competitor strategies, exploring new monetization models and growth opportunities. Adapt pricing and incentive structures based on market conditions to enhance the competitiveness of advertising offerings. 2. Operational System Development & Optimization - Optimize the monetization operations framework, including advertiser education, ad placement strategies, and funnel optimization. - Establish standardized processes and operational mechanisms to achieve automation and intelligent monetization operations. - Plan and execute promotional campaigns to attract advertisers and merchants while increasing their willingness to pay. - Design marketing tools and promotional programs, such as discounts, cashback, and incentive schemes, to boost ad spend and merchant engagement. 3. Data-Driven Growth & Business Decision-Making - Refine key data metrics and analytical frameworks to gain deep insights into advertiser and merchant behaviors, driving continuous strategy iteration. - Develop data tools and analytical models to enhance revenue forecasting, market segmentation, and precision marketing. - Leverage A/B testing and experimental design to improve advertiser efficiency and lifetime value (LTV). - Utilize financial models (e.g., ARPU, LTV, ROI) to develop business optimization plans that maximize revenue potential. 4. Cross-Functional Collaboration and stakeholder management -Work closely with product, technology and commercial teams to ensure the successful execution of monetization strategies. -Drive technological development and innovation in monetization products to enhance revenue efficiency.

1，负责电商数据仓库的ETL流程设计、开发与优化，尤其关注招商、营销活动（含大促）等核心业务场景的数据集成，确保数据的准确性、实时性和为业务决策和AI应用提供高质量数据基础。 2，主导电商领域的数据建模工作，构建满足用户画像、商品分析、营销效果评估等业务需求的多维数据模型，支持精细化运营、个性化推荐和智能决策。 3，与电商业务、招商、营销业务和数据科学等组紧密合作，深入理解业务痛点和增长目标，提供创新的数据解决方案，优化数据处理流程，提升数据赋能业务的能力。 4，参与大数据平台的优化和扩展，探索并应用AI技术（如机器学习、自然语言处理等）提升数据处理效率、数据质量和数据洞察能力，例如智能数据清洗、异常检测、特征工程自动化等。 5，编写高质量的代码和技术文档，确保代码的可维护性、可扩展性和可理解性，并积极参与技术分享和知识沉淀。 1，Responsible for the design, development, and optimization of ETL processes for the e-commerce data warehouse, with a focus on core business scenarios such as merchant acquisition, marketing campaigns (including major promotions), ensuring accurate, real-time, and efficient data transmission, and providing high-quality data foundation for business decisions and AI applications. 2，Lead data modeling efforts in the e-commerce domain, building multi-dimensional data models that meet the business needs of user profiling, product analysis, marketing performance evaluation, etc., supporting refined operations, personalized recommendations, and intelligent decision-making. 3，Collaborate closely with e-commerce business, merchant acquisition, marketing, and other teams to deeply understand business pain points and growth objectives, provide innovative data solutions, optimize data processing workflows, and enhance the ability of data to empower business. 4，Participate in the optimization and expansion of big data platforms, explore and apply AI technologies (such as machine learning, natural language processing, etc.) to improve data processing efficiency, data quality, and data insight capabilities, such as intelligent data cleaning, anomaly detection, and automated feature engineering. 5，Produce high-quality code and technical documentation to ensure code maintainability, scalability, and understandability, and actively participate in technical sharing and knowledge accumulation.