Admission Requirements for Masters in Data Science in USA - India Social Bookmarking Website

The entrance criteria for a Master in Data Science in the United States differ per university. Some particular score criteria for admission to the best universities for masters in data science in usa

University	GRE	TOEFL iBT
Stanford University	328	105
Harvard University	292	120
Yale University	329	100
University of Pennsylvania	Not required	100
John Hopkins University	310	100
University of California, Berkeley	320	90
Columbia University	320	100
University of Michigan—Ann Arbor	Not required	84
New York University	326	110
University of California, San Diego	Not required	85

salary after Master in Data Science USA

After completing a Masters in Data Science in USA, a student may make an average annual income of 155,000 USD. To be a good data scientist, you must understand machine learning, Python, data analysis, and statistical analysis. Some prominent job profiles to pursue following an MS in data science in the United States are:

Job Profile	Average Salary (USD)	Average Salary (INR)
Data Scientists	95,829	79.71 lakhs
Business Intelligence Analyst	74,329	61.82 lakhs
Data Engineer	93,383	77.67 lakhs
Senior Data Analyst	89,124	74.13 lakhs
Analytics Manager	100,817	83.86 lakhs

Students can also work as financial analysts, data analysts, data administrators, business analysts, and in other roles that require managing large amounts of data. Google, Meta, Amazon, Microsoft, and IBM are the top recruiters of MS Data Science graduates in the United States. In addition to master’s degrees in data science, students interested in data management and administration can pursue a Master in Data Science in USA.

Master in Data Science in USA Scope for Indian Students:

After earning Master in Data Science in USA, students can easily obtain a high-paying job in the United States. Students can pursue a variety of career paths, including those of big data engineers, data scientists, database administrators, and data engineers.

Conclusion:

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