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Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing
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Data Science: AI Experiences PhD Internship Opportunities is an internship role where the candidate will own scoped projects from initial problem definition through analysis, validation, and recommendation. The individual will analyze large-scale behavioral, content, commerce, and advertising data to address product and business questions while developing metrics that reflect user experience and sustainable value. Day-to-day tasks involve designing experiments, applying causal inference, statistical modeling, machine learning, and evaluation frameworks. Technical requirements include proficiency in SQL, Python, R, Perl, or C#, along with experience using tools like Excel, MATLAB, AMPL, or SAS. The role involves collaborating with product managers, engineers, and economists to influence decisions based on data findings. Candidates must be pursuing a doctorate in fields such as Mathematics, Statistics, Economics, or Computer Science while working with telemetry systems and A/B testing methodologies.
Own data science projects from initial problem definition through analysis, validation, and final recommendation.
Analyze large-scale behavioral, content, commerce, and advertising data using SQL, Python, or R.
Design, execute, and interpret experiments including success metrics, guardrails, and statistical limitations.
Apply causal inference, statistical modeling, machine learning, and evaluation frameworks to answer business questions.
Develop and improve metrics and monitoring approaches that reflect user experience and sustainable value.
Communicate complex methods, findings, and uncertainties clearly to both technical and nontechnical audiences.
Document work to ensure results are reproducible and actionable for stakeholders.
What we're looking for
Own scoped data science projects from problem definition through analysis, validation, and recommendation.
Analyze large-scale behavioral, content, commerce, and advertising data using SQL, Python, R, or comparable tools.
Design, execute, and interpret experiments including success metrics, guardrails, and statistical limitations.
Apply causal inference, statistical modeling, machine learning, or evaluation frameworks to answer business questions.
Communicate findings and recommendations clearly to both technical and nontechnical audiences.
Currently pursuing a Doctorate Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or a related field.
Must have at least one additional quarter or semester of school remaining after the internship ends.
Enrolled in a full-time bachelor's, master's, MBA, or PhD program in a relevant field during the term before the internship.
Machine Learning
Large-scale Distributed Systems
Data Preparation
Search
Language Models
Recommender Systems
Geospatial
Online Evaluation
Data Quality
Scalable Systems
Python
R
SAS
SPSS
PowerBI
Tableau
Data Warehousing
Predictive Modeling
Linear Models
Multivariate Analysis
Clustering
Bayesian Methods
Scripting
Data Mining
Machine Learning
Large Language Models
Diffusion Models
Reinforcement Learning
Python
Swift
Objective C
Java
TensorFlow
PyTorch
CoreFlow
Linear Algebra
Statistics
Time Series Analysis
Optimization
Causal Inference
Stochastic Modeling