DCS Principal Data & Applied Scientist at Microsoft

DCS Principal Data & Applied Scientist Details

Dec. 7, 2018, 5:14 p.m.
Individual Contributor
Issaquah, WA
Microsoft's Customer Service
How would you like to impact the experience of 800 million users per month? Be on the forefront of digital transformation? Microsoft's Customer Service and Support is transforming how we engage with customers online; we are creating a world class support experience for our customers and empower customers to self-solve more of their issues and be more satisfied with their self-help experience. We are looking for individuals who are passionate about data and want to apply cutting-edge Machine Learning (ML) and Artificial Intelligence (AI) techniques to solve customer self-serve Help problems and improve a world-class end-to-end customer support experience across Microsoft products.

As a Principal Data Scientist, you will serve as a technical lead for the team in applying rigorous scientific methodology, statistics, and algorithms to discover and frame relevant problems, hypotheses, and opportunities, and drive actionable insight, tools, technology, or methods into the product/service development process to achieve the Digital Customer Support goals. You will develop capabilities for deep learning models and tools and solutions around it. You will work on predictive and prescriptive modeling, natural language processing, and text mining and processing, recommendations, clustering,
Basic/Key Qualifications: Master's degree in ML, AI, CS, or a mathematical or scientific field requiring statistical fluency 10 or more years of industry experience, at least 6 years of which must be in analytics, ML, AI, data science, operations research, or data-driven business strategy Significant experience in natural language processing Experience in design of experiments (DoE), applying scientific method to business problems, and hypothesis testing. Ability to synthesize complex issues/scenarios into easy-to-understand concepts Experience in any of the deep learning frameworks (Keras, TensorFlow,
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