Data Science - Forward Deployed Engineer: PhD Internship Opportunities

Microsoft • Redmond, WA

3d

About The Position

Microsoft Frontier Co. is a customer outcome-driven organization that brings together industry expertise, strategic partnerships, and engineering to help customers turn AI into lasting business value. Its teams work alongside customers to co-design, deploy, and continuously improve AI systems that deliver measurable, customer-defined outcomes.

As a Data Science PhD Forward Deployed Engineer Intern, 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 apply current advances in artificial intelligence and data science to problems at scale, collaborating with global organizations across industries. You will develop and evaluate models and translate evidence into decisions, partnering with engineers, product managers, and domain experts from data discovery through deployment. The internship offers the opportunity to contribute to real-world projects with teams around the world. Participation does not guarantee future employment; successful interns may be considered for full-time opportunities, but Microsoft cannot sponsor a work visa for a full-time position associated with this internship.

Requirements

• Currently pursuing a doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or a related field.
• Have at least one academic quarter or semester remaining after completion of the internship.
• Be enrolled in a full-time bachelor's, master's, MBA, or PhD program in a relevant area during the academic term immediately before the internship.

Nice To Haves

• At least 2 years of programming experience in data science, machine learning, statistical computing, or a related technical area.
• At least 1 year of experience delivering data science or machine learning projects in collaborative, cross-functional teams.
• At least 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 data science programming languages 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.

Responsibilities

• Prepare and assess data using querying, visualization, and reporting techniques to identify key attributes, data quality considerations, and project impact.
• Develop, train, optimize, and evaluate models using suitable 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 AI system and product performance.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Education Level: Ph.D. or professional degree