Principal Applied Scientist, Viva Engage

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Viva Engage connects people through communities, bringing leaders and employees together to share knowledge, clarify priorities, and build relationships. Viva Engage (formerly Yammer) is the premier tool to create multi-directional dialogue between tens of millions of employees worldwide every month.

Engage team members are at the forefront of driving artificial intelligence (AI) applications and copilot adoption to make communication and information sharing easy and authentic. Our work supports top challenges for our customers, including digital safety, trusted security standards, and deep analytics to help our customers maximize reach, reduce inefficiencies, and create a thriving organizational culture. We would love to have you join the team driving innovation, connection, and community for our valued global customers.

As a Principal Applied Scientist at Viva Engage, your role is to build predictive models that connect individuals with each other and knowledge across organizations. Our focus lies in discovery, recommendations, and relevance across Viva Engage, leveraging data from our platform and across Office 365.

This role presents an opportunity to create a vision around the Viva Engage machine learning platform and help us make it a reality. Our tight-knit, high-performing team, coupled with the unique challenges posed by social enterprise analytics, will offer plenty of opportunities for impact.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Required Qualifications:

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
  • OR equivalent experience.
• 2+ years of experience working on Machine Learning models specifically with Natural language-based models and vector databases.

Preferred Qualifications:

• Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
  • OR equivalent experience.
• 5+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).
• 2+ years experience presenting at conferences or other events in the outside research/industry community as an invited speaker.

Applied Sciences IC5 - The typical base pay range for this role across the U.S. is USD $137,600 - $267,000 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $180,400 - $294,000 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

Microsoft will accept applications and processes offers for these roles on an ongoing basis.

#VivaEngage #MSFTNSBE25

• Build and iterate on machine learning models to power recommendations for the Viva Engage Feed.
• Develop AI Agents to assist with tasks to productivity through automation and intelligent recommendations.
• Work with large, complex data sets, solving difficult, non-routine analysis problems with advanced analytical methods.
• Utilize Large Language Models (LLMs) for advanced text analysis and natural language understanding tasks, enabling deeper connections and knowledge sharing across organizations.
• Leverage generative AI techniques to enhance data augmentation and predictive capabilities, further improving recommendations and personalized user experiences.
• Develop deep product intuition to influence future product roadmaps and drive decision-making.
• Collaborate with product and engineering to craft experiments and test hypotheses.
• Use communication skills to distill complex technical work for audiences of all levels and across multiple functional areas.
• Navigate complex situations and influence across multiple product areas by leveraging leadership acumen.