微软Senior Data & Applied Scientist
任职要求
Required Qualifications: • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)• OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techn • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical tec • OR equivalent experience. • 2+ years customer-facing, project-delivery experience, professional services, and/or consulting experience • 4+ years applied ML/NLP experience delivering models and features to production at scale. • Software engineering excellence:• Proficiency in Python and PyTorch (or equivalent DL framework). • Solid SDLC practices: unit/integration testing, CI/CD, code reviews, version control, performance profiling, and reliability hardening. • Ability to write clean, maintainable, efficient code for production services and clients. • Experimentation & evaluation: sound experimental design, metric design (quality, safety, latency, cost), and statistical analysis; experience running online A/B tests. • Proven collaboration with PM & Engineering to integrate ML into shipped product (APIs/services/clients) and to drive measurable user or business impact. Preferred Qualifications: • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science,• OR related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, • OR related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, • OR related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) • OR e…
工作职责
• 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.
1.Lead merchant-side analysis for food delivery business, supporting frontline operations in business understanding, marketing campaigns, product experience optimization, merchant research, and strategy formulation to enhance operational efficiency. 2.Identify business needs and build scalable indicator systems for scenarios including performance analysis, business monitoring, and team management. Design and maintain data dashboards and data products to improve data accessibility for cross-functional teams. 3.Conduct deep-dive analysis using advanced analytics tools/methods to uncover actionable insights, identify growth opportunities, and address critical business challenges to drive optimization. 4.Deliver thematic studies to provide data-driven recommendations for executive decision-making, product roadmaps, and business strategies. 5.Collaborate with cross-functional teams (Operations, Product, Engineering, Algorithms) to execute data-driven strategies and ensure measurable business impact. 1.负责外卖业务商家侧分析，支持前线的业务理解、营销活动、产品体验、商家研究、策略制定等，提升整体运营效率； 2.洞察业务需求，建设在经营分析、业务监控、团队管理等不同场景下的指标体系，搭建和维护数据看板，建设数据产品，提升前后线团队的数据使用效率和便捷性； 3.深入理解业务，运用数据分析工具和方法，挖掘数据背后信息，产生业务洞察，发现机会点，回答业务的关键问题，驱动业务优化迭代； 4.通过专题分析，对具体业务问题进入深入分析，为公司运营决策、产品方向、业务策略提供专业意见和信息输入； 5.与前线、运营、产品、算法、技术等团队协同合作，推进策略的落地执行，为业务结果负责。
* Maintain comprehensive compliance program for PCI-DSS * Conduct regular internal data security audit and oversee the implementation of corrective actions * Partner with Legal, Product and other teams in both group and local level to ensure GDPR compliance (e.g. Cookie, DSR, DPIA ) * Develop and enforce local security policies and procedures that in line with ISMS * Promote security awareness through training, workshops and internal communications * Support data security incident response and facilitate preventive measure to reduce the likelihood * Daily security support to business teams
Tabulate service operation report, objectively & truthfully present operation results.Revise Customer Support Center desired objectives, establish corresponding data indices and models to monitor thereof.Maintain and analysis key data indices provide suggestions and proposals on Customer Support Center operation and project development.Make continuous efforts on operations of the department, find problems, or provide prediction and early warning based on deep statistical analyses.Provide support on design and creation of reports of various types;Propose better solutions on each team’s effective analysis and reports.Give leads on automation project in order to lessen workload of reports and data consolidation.Develop new tools when necessary.
测量和分析（Measurement & Analytics）团队是优化我们国际化大规模营销预算的关键参与者。 您将加入一个由热情的数据科学家和分析师组成的专业团队，为国际化业务提供最佳营销建议。 作为数据科学家，您将负责支持创新解决方案的开发、挑战行业现状并通过高级数据自动化扩展解决方案。 覆盖 10 +国家和 业务线，您将接触到许多合作方，他们是各自领域的专家。 快速迭代和不断学习将是这一旅程的关键部分。 如果您喜欢从0到1的创造，持续的学习进步的机会，国际化的团队氛围和灵活的办公环境，与多元化的顶尖人才团队合作，那么这可能是您的理想工作！ 你的责任 ● 您将成为消费者分析中所有形式的营销归因和衡量（Marketing Attribution & Measurement )的专家，就营销衡量框架(Marketing Measurement Framework)向其他数据分析师和营销团队提供专家建议。 ● 与其他数据分析师和分析工程师密切合作，制定和执行数据科学发展规划的路线图，将一流的衡量框架投入生产。 ● 您的工作将主要集中在开发一流的营销衡量流程和框架（包括Marketing Mix Modeling, Attribution and Incrementality Test/Geo Lift Test, etc），这将作为我们营销策略的基石，使团队能够 跨营销渠道和市场做出更明智的投资决策。 ● 您还将致力于建立统计/机器学习模型来预测用户生命周期价值（LTV 模型）和其他创新数据科学项目。 ● 您将是数据布道师，宣传数据的使用并主动发现机会以提高整个组织的数据素养和参与度。