Data Science: PhD Internship Opportunities – Redmond

Overview: 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. Data Scientist PhD Interns at Microsoft, you will use machine learning, statistics, experiments, and/or AI, LLM, SLM and agents and more to build and improve great products while making business impact. As a Data Scientist intern you will collaborate with stakeholders, formulate approaches to solve problems and use algorithms and data sources in the context of business and engineering needs. You will also be able to combine your engineering abilities with analytical skills to make customer experiences better. Our Data Scientists use innovative methods, algorithms, and tools daily to drive results throughout Microsoft devices, operating systems, products, and services and provide novel insights into business and customer scenarios. As an intern at Microsoft, you’re stepping into a world of real impact from day one. You’ll collaborate with global teams on meaningful projects, explore cutting-edge technologies like AI, and kick start your career while doing it. With a strong focus on learning and development, this is your opportunity to grow your skills, build community, and shape your future—all while being supported every step of the way. 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 and 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. Please note this application is only for internships based in our Redmond, Washington office. For internships in other offices in the United States, please see our Careers site. #EiP #phd

Qualifications: Required Qualifications: Currently pursuing a Doctorate Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field. Must have at least one additional quarter/semester of school remaining following the completion of the internship. Candidate must be enrolled in a full time bachelor's, masters, MBA, or PhD program in area relevant for the role during the academic term immediately before their internship. Other Requirements: Ability to submit an official or unofficial academic transcript as part of the evaluation process, if selected for interviews. Preferred Qualifications: Some Engineering experience and or project course work using large data systems on SQL, Hadoop, etc. Proficiency using one or more programming or scripting language to work with data such as: Python, Perl, or C#. Some experience and or project course work performing data analysis and applying statistics working with tools such as: Excel, R, MATLAB, AMPL, or SAS. Some experience and or project course work with product and service telemetry systems. Some A/B Testing or experimentation (this can be from conducting real life science experiments, hypothesis testing in stats etc.). Some experience or course work applying basic ML to a type of data and or used algorithms to conduct experiments on data. The base pay range for this internship is USD $6710.00 - $13270.00 per month. 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 $8760.00 - $14360.00 per month. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-intern-pay Microsoft accepts applications and processes offers for these roles on an ongoing basis.

Responsibilities: Formulate approaches to solve problems using well defined algorithms and data sources. Incorporate an understanding of product functionality and customer perspective to provide context for those problems. Use data exploration techniques to discover new questions or opportunities within your problem area and propose applicability and limitations of the data. Interpret the results of their analysis, validate their approach, and learn to monitor, analyze, and iterate to continuously improve. Engage with peer stakeholders to produce clear, compelling, actionable insights that influence product and service improvements that will impact millions of customers. Participate in the peer review process and act on feedback while learning innovative methods, algorithms, and tools to increase the impact and applicability of your results.

Benefits: Industry leading healthcare