亚马逊Data Scientist, Data Intelligence, Professional Services GCR
任职要求
基本任职资格 - Master's or Ph.D. degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field. - 4+ years of experience in developing and deploying machine learning models, with a strong focus on generative AI techniques. - Proficiency in programming languages such as Python, PyTorch, or TensorFlow, and experience with deep learning frameworks. - Strong background in natural language processing, computer vision, or multimodal learning. - Ability to communicate technical concepts to both technical and non-technical audiences. 优先任职资格 - Experience with large language models, such as Claude, GPT, BERT, or T5. - Familiarity with reinforcement learning techniques and their applications in generative AI. - Understanding of ethical AI principles, bias mitigation techniques, and responsible AI practices. - Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and distributed computing frameworks (e.g., Apache Spark, Dask). - Strong problem-solving, analytical, and critical thinking skills. - Strong communication, collaboration, and leadership skills. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
工作职责
1. Generative AI Model Development: -Design and develop generative AI models, including language models, image generation models, and multimodal models. -Explore and implement advanced techniques in areas such as transformer architectures, attention mechanisms, and self-supervised learning. -Conduct research and stay up-to-date with the latest advancements in the field of generative AI. 2. Data Acquisition and Preprocessing: -Identify and acquire relevant data sources for training generative AI models. -Develop robust data preprocessing pipelines, ensuring data quality, cleanliness, and compliance with ethical and regulatory standards. -Implement techniques for data augmentation, denoising, and domain adaptation to enhance model performance. 3. Model Training and Optimization: -Design and implement efficient training pipelines for large-scale generative AI models. -Leverage distributed computing resources, such as GPUs and cloud platforms, for efficient model training. -Optimize model architectures, hyperparameters, and training strategies to achieve superior performance and generalization. 4. Model Evaluation and Deployment: -Develop comprehensive evaluation metrics and frameworks to assess the performance, safety, and bias of generative AI models. -Collaborate with cross-functional teams to ensure the successful deployment and integration of generative AI models into client solutions. 5. Collaboration and Knowledge Sharing: -Collaborate with data engineers, software engineers, and subject matter experts to develop innovative solutions leveraging generative AI. -Contribute to the firm's thought leadership by presenting at conferences, and participating in industry events.
• 3+ years of experiences in a data science role - preferably in the digital advertising industry, as a data scientist, consultant or business analytics professional. • Programming skills in Python and SQL, comfortable with advanced analytics tools such as R, Spark, and Tableau • Experience with in-person client interactions, specifically senior-level executives, and knowledge to also work with business intelligence and data science experts • Ability to communicate and distill information from large data sets and results into simple concepts and actionable insights for a variety of audiences, such as business and leadership teams, to influence sales and marketing strategy • Deep knowledge of advanced analytical techniques and statistical methods, including regression, classification, clustering, etc. • A strong passion for business intelligence and analytics with the ability to work closely with the business teams, understand business requirements, and manage complex projects related to data-driven initiatives
A successful candidate will have deep experience in applied methods (statistical analysis, predictive modeling, classification, impact measurement), experience building reporting dashboards, and using those methods and tools to drive key business insights. These insights include but not limited to market growth opportunities and strategies, product opportunities, and advertiser behaviors. The role requires data science skills (i.e., a broad knowledge of existing data mining algorithms), strong business acumen, and knowledge on mobile ads market. You’ll work closely with a broad range of data professionals as well as business leaders. You’ll be working on projects where tools and methods are used to drive real-world business value. - Support DI, Product, Marketing, Partner Development with analytics for customer insights and product opportunity areas. - Quantify the impact of product, sales, and marketing initiatives on customer happiness, and future behavior. - Manage business analytic projects through all phases, including data quality, data modeling, algorithm/KPI development, statistical analysis, data visualization, and presentation of results and deliverables. - Monitor usage metrics, understanding business-based explanations for large scale trends, and patterns in customer lifecycle behavior.
Introduction Hiring manager and Recruiter should collaborate to create the relevant verbiage. Your role and responsibilities Seeking new possibilities and always staying curious, we are a team dedicated to creating the world’s leading AI-powered, cloud-native software solutions for our customers. Our renowned legacy creates endless global opportunities for our IBMers, so the door is always open for those who want to grow their career. IBM’s product and technology landscape includes Research, Software, and Infrastructure. Entering this domain positions you at the heart of IBM, where growth and innovation thrive Required education Bachelor's Degree Preferred education Master's Degree
• Define and deliver large-scale BI solutions, including data modeling, KPI standardization, and pipeline automation. • Lead migration of legacy reporting into modern AWS QuickSight and other BI platforms. • Establish and maintain data foundations for social and marketing data, ensuring completeness, accuracy, and compliance. • Conduct advanced analytics, including user behavior modeling, segmentation, and marketing campaign measurement. • Generate actionable insights and recommendations to improve seller journeys, marketing effectiveness, and AI agent performance. • Collaborate with marketing operation team, data engineers, product managers, SDEs, financial analysts, and data scientists to design metrics and guide business decisions. • Drive best practices in operational excellence, data quality management, and data governance. A day in the life You will define marketing BI strategy, build scalable data models and generate actionable insights that drive product, marketing, and AI initiatives. You will partner with data engineering, product, and science teams to ensure high-quality, compliant, and scalable data foundations. Your work will directly influence AI-powered agents, seller engagement, and business growth.