Provides technical leadership for AI-native software engineering by driving adoption of Responsible AI practices, improving AI-enabled development processes, establishing engineering quality measures, mentoring teams on AI-assisted development, and ensuring AI-generated assets meet security, compliance, and quality standards. Owns architecture, engineering excellence, and software quality across complex products by leading system design, code quality strategies, testing frameworks, dependency management, performance optimization, security reviews, and scalable engineering practices while mentoring engineers across teams. Leads secure delivery, operational readiness, and platform reliability by defining deployment and rollback strategies, driving automation and observability, establishing security-by-design principles, managing experimentation frameworks, leading incident response and live-site operations, and ensuring products meet reliability, privacy, compliance, and disaster recovery

requirements. Drives cross-team execution and customer-focused innovation by partnering with stakeholders to shape product

requirements, align roadmaps, resolve dependencies, incorporate customer and telemetry insights, establish success metrics, and deliver secure, scalable, and highly available solutions that create measurable customer value. 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 techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 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 Experience with machine learning algorithms for forecasting, clustering, classification, recommendation systems, NLP, etc.

Yammer is an enterprise social network established to foster team collaboration, empower employees, and drive business transformation. It enables employees to collaborate in real time across departments, geographies, and business applications. It also helps them create groups to collaborate on projects and share and edit documents.

The service of yammer.com can be accessed through the web, desktop, and mobile devices including iPhone, iPad, Windows Phone, Android, and Blackberry, enabling a “virtual office” that employees can plug into while on-the-go. Additionally, Yammer can be easily integrated with other systems such as Microsoft SharePoint, creating a social layer across all enterprise applications.

Yammer has secured more than 7 million users, including employees from 85 percent of the Fortune 500 companies. Founded in 2008, Yammer is now a part of Microsoft.

Senior Data Scientist

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