Job Category: Software Engineering: Development
Location: Redmond, WA, US
Job ID: 850173-122324
Division: Cloud and Enterprise Engineering
Description
Online commerce has become a critical capability for practically every business at Microsoft. As we transition from on premise software sold via traditional retail and enterprise sales channels to a Devices and Services company, the ability to perform online commerce becomes an essential element for success. Whether renting a movie or buying a game on Xbox LIVE, purchasing an app on a Windows or Windows Phone device, signing up for an Office 365 subscription or paying for Azure services, a reliable commerce service is crucial.
The newly formed Knowledge Services team in the Commerce Platform organization is responsible for Commerce Big Data/analytics, business intelligence, anti-fraud services and tools, and experimentation platform. Strategic imperatives include modernizing the BI and anti-fraud infrastructure utilizing Big Data platforms, enabling Commerce and our partners to make more & better decisions based on data and bringing data sciences such as machine learning to bear on our anti-fraud and other services. The Commerce Platform is uniquely positioned at Microsoft to have a view across service businesses of Microsoft, and have a common view of the customer across Microsoft services, including a deep understanding of their wants, needs and purchase preferences. In the past few years, more of the world has been shifting to leverage Big Data platforms to derive & leverage deep insights to continuously improve their products, their customer experiences, their businesses, their processes and tools. This ability to leverage insights to improve and compete is now a key ingredient & differentiator to win in today’s world. The stakes for Commerce Platform & the Knowledge Services Team to provide value to Microsoft businesses and help them make better decisions based on data & insights has never been higher.
We are staffing up this new team with talented and experienced engineers with proven strengths in technical innovation, technical design and architecture, data sciences, cross-group collaboration, shipping complex products/Services, and engineering excellence. This team will focus both on large scale engineering challenges (data platforms/services) and algorithmic challenges (machine learning, data mining, predictive analytics, etc.). We are a combined engineering organization that manifests authority, responsibility and accountability for all aspects of the running service (not just the software that powers it) lower in the organization. We will optimize for engineering agility and service availability by adopting a Service Oriented Engineering approach.
We are looking for talented engineers with a strong data sciences/machine learning background that can drive critical areas in this exciting new space.
Qualifications
• Deep understanding of statistical modeling / machine learning / data mining concepts, and a track record solving problems with these methods.
• Experience/knowledge with various machine learning tools and libraries, data mining tools, and statistical packages.
• Prior experience working with large-scale datasets using big data techniques (such as Hadoop, MapReduce, NoSQL, etc.).
• 3+ years of experience writing code to implement machine learning and data mining algorithms, including regression analysis, clustering, and classification. Experience with data visualization a plus.
• Master's degree in Statistics, Machine Learning, Computer Science, Electrical Engineering, Applied Mathematics, or a related field (PhD preferred).
ST:OCP
Nearest Major Market: Seattle
Nearest Secondary Market: Bellevue
Job Segments: Developer, Engineer, Electrical, Software Engineer, Computer Science, Technology, Engineerin
g
Location: Redmond, WA, US
Job ID: 850173-122324
Division: Cloud and Enterprise Engineering
Description
Online commerce has become a critical capability for practically every business at Microsoft. As we transition from on premise software sold via traditional retail and enterprise sales channels to a Devices and Services company, the ability to perform online commerce becomes an essential element for success. Whether renting a movie or buying a game on Xbox LIVE, purchasing an app on a Windows or Windows Phone device, signing up for an Office 365 subscription or paying for Azure services, a reliable commerce service is crucial.
The newly formed Knowledge Services team in the Commerce Platform organization is responsible for Commerce Big Data/analytics, business intelligence, anti-fraud services and tools, and experimentation platform. Strategic imperatives include modernizing the BI and anti-fraud infrastructure utilizing Big Data platforms, enabling Commerce and our partners to make more & better decisions based on data and bringing data sciences such as machine learning to bear on our anti-fraud and other services. The Commerce Platform is uniquely positioned at Microsoft to have a view across service businesses of Microsoft, and have a common view of the customer across Microsoft services, including a deep understanding of their wants, needs and purchase preferences. In the past few years, more of the world has been shifting to leverage Big Data platforms to derive & leverage deep insights to continuously improve their products, their customer experiences, their businesses, their processes and tools. This ability to leverage insights to improve and compete is now a key ingredient & differentiator to win in today’s world. The stakes for Commerce Platform & the Knowledge Services Team to provide value to Microsoft businesses and help them make better decisions based on data & insights has never been higher.
We are staffing up this new team with talented and experienced engineers with proven strengths in technical innovation, technical design and architecture, data sciences, cross-group collaboration, shipping complex products/Services, and engineering excellence. This team will focus both on large scale engineering challenges (data platforms/services) and algorithmic challenges (machine learning, data mining, predictive analytics, etc.). We are a combined engineering organization that manifests authority, responsibility and accountability for all aspects of the running service (not just the software that powers it) lower in the organization. We will optimize for engineering agility and service availability by adopting a Service Oriented Engineering approach.
We are looking for talented engineers with a strong data sciences/machine learning background that can drive critical areas in this exciting new space.
Qualifications
• Deep understanding of statistical modeling / machine learning / data mining concepts, and a track record solving problems with these methods.
• Experience/knowledge with various machine learning tools and libraries, data mining tools, and statistical packages.
• Prior experience working with large-scale datasets using big data techniques (such as Hadoop, MapReduce, NoSQL, etc.).
• 3+ years of experience writing code to implement machine learning and data mining algorithms, including regression analysis, clustering, and classification. Experience with data visualization a plus.
• Master's degree in Statistics, Machine Learning, Computer Science, Electrical Engineering, Applied Mathematics, or a related field (PhD preferred).
ST:OCP
Nearest Major Market: Seattle
Nearest Secondary Market: Bellevue
Job Segments: Developer, Engineer, Electrical, Software Engineer, Computer Science, Technology, Engineerin
g
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