Senior Data Scientist

Microsoft Dynamics 365 is a suite of easy-to-learn and easy-to-use business solutions tailored to any market, designed for any business size, and dedicated to growing business through happy customers. The Customer Service Applications Team delivers business applications for Connected Customer Care for Contact Centers! Our team is at the forefront of digital transformation, empowering organizations to revolutionize their customer service and contact center operations through cutting-edge AI solutions and product offerings, represents a new era of applications that harness the power of data, AI, and productivity tools to deliver unparalleled experiences across all channels.  

We are looking for a Senior Data Scientist to join our team. 

In this role in the Microsoft Dynamics Customer Service Application team, you will work with business and AI leaders as well as internal business users and Partners to understand, explore and develop AI/ML solutions to solve their business needs. 

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 Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years experience in business analytics, data science, software development, data modeling or data engineering work 
  • OR Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 3+ year(s) experience in business analytics, data science, software development, or data engineering work 
  • OR equivalent experience. 

• 1+ year(s) of experience building generative AI applications.
• 1+ year (s) of experience fine-tuning language models. 

Other Requirements:

• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: 
• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

Preferred Qualifications:

• Experience with design and implementation of enterprise-scale AI products  
• Experience delivering Dynamics 365 and/or Power Platform solutions desirable   

Data Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $158,400 - $258,000 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 for the role until June 25, 2025. 

#BICJobs

In this role you will be collaborating with a team of applied scientists and software engineers to implement these solutions and enhance customer experience, be responsible for implementing AI features towards a wide variety of business problems within Dynamics 365 products portfolio as well as ensuring they are done to meet rigorous quality standards with the result being software that is used by individuals and businesses throughout the world. 

• Focus on particular aspects of our product, developing extensive knowledge in the domain and technical framework, notably in Large Language Models (LLM), and play a role in advancing product development through ongoing awareness of industry trends and technologies. 

• Assess business needs and integrate research to achieve business objectives. Your role involves guiding the selection of data to address issues strategically, leveraging your expertise to design, measure and build AI applications to drive tangible business results. 

• Record ongoing work and experimental findings, sharing them to encourage innovation. 

• Assess the effectiveness of models and collaborate with product teams to design AI-driven experiences.