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Profile evaluation for Fall 2022, unconventional background please help!

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Gender Male

Ethnicity : Indian

Undegrad Institution : University of Delhi (tier 2 college)

Major Economics

GPA 7.12/10 (3.6 US equivalent)

Relevant Courses 

Math/Statistics : Math Econ I (7) ,Math Econ II (8) , Statistics (7), Introductory Econometrics (8), Applied Econometrics (10) 

All grades are out of 10, the two math courses covered some linear algebra and the rest was multivariable calculus but did not have vector calculus stuff like green's theorem. The statistics course was calculus based and had random variables, hypo testing, clt and similar stuff. Econometrics was mostly regression stuff.

Graduate Institution : Indian Statistical Institute

Major Quantitative Economics ( MS in QE)

Grade 85.95/100 (For three semesters.)

Relevant Courses Math Methods (95), Statistics (95), Game Theory (91), Probability Theory (66), Econometric Methods - I (90), Game Theory - II(98), The Theory of Mechanism Design(92), Real Analysis(100), Time Series Analysis(77), Econometric Methods - II(78).

All grades are out of 100.

General GRE : Quant(168), Verbal(158)

GRE Mathematics Subject Test : Not given yet.

Research Experience: None so far.

Work Experience:  Working for one of the big four firms. My job mainly has to do with validation of credit risk models for banks(our usual clients). I generally get to work with regression models like linear regression and beta regression, additionally also with logistic regression.

I have done a personal project in which I used a boosting algorithm for a prediction problem and another in which I used deep learning to create a facial expression recognition system. I have also done the deep learning specialization on coursera. Not sure how helpful this stuff is.

The things that I worry about are that my UG institute wasn't really the best in the country, it wasn't a bad school but just wasn't amongst the top colleges, my GPA in UG is also not fabulous however I think it is still better in the relevant courses.  Will bad grade in probability theory, time series analysis and econometric methods - II be a significant factor?


LOR One will be from my game theory and Mechanism Design professor who is a PhD in industrial engineering, rest all will be from other professors. Can't say anything about the quality of the LORs, I hope they will be good.


I want to apply to MS Statistics for Fall 2022 in US. The things I worry the most about are my low grades in Probability Theory, Time Series Analysis and Econometric Methods - II. Can you also tell me how important a role will the SOP play in my applications? Additionally, do I need to give the GRE again to get 170 in quant, is the 168 going to be a big problem at many schools?

My goal is to be able to find a good job as a data scientist, I would like to move into machine learning later on in my career after gaining some experience working as a data scientist.

I have shortlisted the following schools right now, let me know if any schools need to be removed or added and if the list looks reasonable. Please also let me know of some schools that will be easy to get into and will help me find a good job easily. 

Reach: University of Washington, UW Madison

Match: TAMU, University of Minnesota Twin Cities, Purdue University, UCLA, UC Davis, UC San Diego, UIUC, Georgia Tech's(Industrial Engineering with specialization in statistics)

Safety: Stony Brook, Rice University, UC Irvine




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