Skip to main content
Tallo logoTallo logo

Find Jobs

Find Jobs Near You – Available Work in Your Location

Skip to job details

Back to Results

Apply for this opportunity

To apply for this job, you'll continue to an external website or email application.

Microsoft

Data Science - Forward Deployed Engineer: PhD Internship Opportunities

Review key factors to help you decide if the role fits your goals.
Pay Growth
?
out of 5
Not enough data
Not enough info to score pay or growth
Job Security
?
out of 5
Not enough data
Calculating job security score...
Total Score
87
out of 100
Average of individual scores

Were these scores useful?

Job Description

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. Currently pursuing a Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or a related field, with at least one academic quarter or semester remaining after completion of the internship. 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.