- MS, Ph.D., or BS
- 12+ yrs of industry experience.
- Building and owning production machine learning models to improve results
- Finding insights and forming hypothesis on large-scale data with various machine learning, feature engineering, statistical, and data mining techniques: e.g. regression, classification, NLP, optimization, p-values analysis
- Designing experiments, understanding the resulting data, and producing actionable, trustworthy conclusions from them
- Wrangling large amounts of data (think petabytes) using various tools, including open-source ones and your own. All programming languages are welcome, especially Python, C#, R, C++, Java, and SQL
- Taking complex problems and the associated data and giving the answers in a concise form to assist senior executives in making key business decisions Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.Industry leading healthcareEducational resourcesDiscounts on products and servicesSavings and investmentsMaternity and paternity leaveGenerous time awayGiving programsOpportunities to network and connect
Principal Applied Scientist - Bengaluru, India - Microsoft
Description
Overview
We are looking for a highly skilled Principal applied scientist with a strong background in Machine Learning, Reinforcement Learning, Causal Inference, Data Science, Data Mining, or related fields. Candidates should be passionate about artificial intelligence and optimization at web scale. They will play a key role in driving algorithmic improvements to online and offline systems, develop and deliver robust and scalable solutions, make direct impact to both user and advertisers experience, and continually improve our KPIs.
The Search + Distribution organization includes the product, engineering, and growth teams responsible for Microsoft Bing worldwide, as well as Microsoft Search in Bing for enterprise. Our mission is to delight users everywhere with the best search experience. We are focused on creating competitive and differentiated search quality experiences, which we do by applying highly advanced ML technologies such as large-scale deep learning models and by investing in more modern search experiences.
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Responsibilities