Data Science - Forward Deployed Engineer: PhD Internship Opportunities

Come build community, explore your passions and do your best work at Microsoft with thousands of University interns from every corner of the world. This opportunity will allow you to bring your aspirations, talent, potential, and excitement for the journey ahead. 

Microsoft Frontier Co. is a new line of business and one of the industry's first customer outcome-driven organizations, bringing together industry expertise, strategic partnerships and engineering as part of Microsoft Customer and Partner Solutions Its teams will work side-by-side with customers to co-design, deploy, and continuously improve AI systems that deliver measurable, customer-defined outcomes. The organization is built around end-to-end Frontier Transformation, helping customers turn AI into real, lasting business value. For those joining, it's a chance to help build a new growth engine for Microsoft and shape how the industry moves from delivering technology to delivering outcomes.  

Step into a role where your ideas spark innovation and your impact is felt every day. As part of Frontier Co, you will work with real-world datasets to develop scalable, production-ready solutions and run experiments that inform business strategy and customer outcomes. You will collaborate with global organizations across industries and apply current advances in artificial intelligence and data science to solve problems at scale. 

As a  Data Science PHD Forward Deployed Engineer Intern, you will develop models, evaluate results, and translate evidence into decisions that support measurable business outcomes. You will partner with engineers, product managers, and domain experts throughout the lifecycle from data discovery through deployed solutions. Join the team to help organizations realize greater value from their data. 

At Microsoft, Interns work on real-world projects in collaboration with teams across the world, while having fun along the way. You'll be empowered to build community, explore your passions and achieve your goals. This is your chance to bring your solutions and ideas to life while working on cutting-edge technology. 

At Microsoft, our mission to empower every person and every organization on the planet to achieve more guides how we partner with customers to deliver trusted, impactful solutions. With a growth‑mindset culture, we innovate responsibly and measure success by shared progress, people, teams, and customers. Join us to do meaningful work that changes the world and helps shape what’s next for everyone. 

Participation in this internship does not guarantee future employment. While successful interns may be considered for full-time opportunities, Microsoft is unable to sponsor a work visa for any full-time position associated with this internship due to the nature of the role's job duties. 

• Prepare and assess data by using querying, visualization, and reporting techniques to identify key attributes, quality considerations, and project impact. 

• Develop, train, optimize, and evaluate models using appropriate statistical and machine learning approaches to address business objectives. 

• Design and analyze controlled experiments, communicate findings to stakeholders, and connect technical metrics with business outcomes. 

• Partner with engineering teams to operationalize models, supporting performance, scalability, monitoring, maintenance, and integration into production systems. 

• Collaborate with cross-functional partners to define evaluation metrics and improve artificial intelligence system and product performance. 

• 2+ years of programming experience in data science, machine learning, statistical computing, or a related technical area. 

• 1+ year of experience delivering data science or machine learning projects in collaborative, cross-functional teams. 

• 2+ years of experience developing and applying statistical methods, machine learning algorithms, data structures, or optimization techniques. 

• Coursework, research, or applied experience in machine learning, statistical modeling, experimentation, causal inference, data mining, databases, data engineering, or distributed systems. 

• Experience with SQL and programming languages commonly used in data science, such as Python, R, Java, Scala, C#, or similar. 

• Familiarity with data pipelines, large-scale data processing frameworks, model evaluation, telemetry systems, visualization or reporting tools, or cloud-based data and machine learning platforms. 

• Interest in large-scale data science, machine learning systems, experimentation, model optimization, data quality, and translating analytical findings into business and customer impact. 

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