亚马逊Senior Data Scientist, Amazon Global Selling -AIT
任职要求
基本任职资格 - 8+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience - 6+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science - Experience with statistical models e.g. multinomial logistic regression - 5+ years of hands on experience with Python to build, train, and evaluate models 优先任职资格 - 2+ years of data visualization using AWS QuickSigh…
工作职责
• Collaborate with BIE,DE, PM, CSM to research, design, develop, and evaluate generative AI solutions to address Global Selling challenges. • Interact with stakeholders directly to understand their business problems, aid them in implementation of generative AI solutions, brief stkaholders and guide them on adoption patterns and paths to production • Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder
【数据研发/数据分析方向】 1. 负责国际化出行（拉美、亚太、中东等）用户增长、用户运营、广告投放，支持全球多国家/多时区/多币种数据模型。 2. 熟悉数仓架构（ODS→CDM→ADS），确保数据质量、一致性及可扩展性，丰富业务应用层集市，构建业务数据门户，提升数据分析、业务决策的效率。 3. 与增长产品经理、策略运营深度协同，将埋点、用户行为、营销花费、补贴效果等数据沉淀为可复用的增长数据资产。 4. 构建实时+离线数据体系，支持用户画像的实时获取，以及实时计算用户平台价值。 5. 制定并落地数据治理规范（口径、生命周期、成本、权限、合规），满足 GDPR/CCPA/当地数据出境要求。 6. 建立数据异常检测与自动修复机制，保障核心指标（ROI、CAC、留存、LTV）的准确性与及时性。
• Ship features with PM & Engineering. Co‑own scenario goals; translate product requirements into scientific plans and productionized solutions that meet quality/latency/cost targets. • Model development & optimization. Design, fine‑tune, and evaluate models for LLM‑based authoring, summarization, reasoning, voice/chat, and personalization (e.g., SFT, alignment, prompt/tool use, safety filtering, multilingual & multimodal). • Data & evaluation at scale. Build/extend data pipelines for curation/labeling/feature stores; author offline eval harnesses; run online A/Bs and interleavings; define guardrails and success metrics; author scorecards and decision memos. • Production ML engineering. contribute to service code and configs; add monitoring, tracing, dashboards, and auto‑scaling; participate in on‑call and postmortems to improve live‑site reliability. • Responsible AI. Produce review artifacts, document mitigations for safety/privacy/fairness, support red‑teaming and sensitive‑use checks, and align with Microsoft’s Responsible AI Standard. • Collaboration & mentoring. Partner across PM/ENG/Design/CE/ORA/CELA; share methods and code, review PRs, improve reproducibility and documentation; mentor junior scientists.
• Lead initiatives to analyze game performance, aiming to boost overall long term performance of Clash of Clans • Enhance experimentation capabilities through sound experiment design and the use of key statistical methods, including causal inference, econometrics, Bayesian modeling, and A/B testing. • Partner with the Game Design, LiveOps, and Monetization teams to analyze game performance, providing clear insights to guide the game’s future direction. • Foster a hypothesis-driven insights culture within the team, strengthening decision-making across Supercell. • Mentor fellow team members, enhancing their technical skills, communication abilities, and collaboration effectiveness.
• Providing Ethernet and routing expertise to customers during project delivery to design, architect and test Ethernet networking solutions. • Work on multi-functional teams to provide Ethernet network expertise to server infrastructure builds, accelerated computing workloads and GPU enabled AI applications. • Crafting and evaluating DevOps automation scripts for network operations, crafting network architectures, and developing switch fabric configurations. • Implementing tasks related to network configuration and validation for data centers. • Create Methods of Procedure and deployment documents. • Use software tools to validate and monitor network performance.