Ramen_Shop

Hey guys, my chances aren't looking that great tbh lol. I want a more applied/professional/career focused curriculum and so I'm trying to decide between the following: Accepted: USC Marshall Business Analytics Rejected: UPenn MSE Data Science Harvard MS Data Science MIT Sloan MBAn (Was really hoping to get into this one but didn't even get an interview so hey, I'm just not good enough. It is what it is) Stanford ICME MS Data Science Track Waiting/Applied: UChicago MS Analytics Columbia MS Data Science UCLA MS Business Analytics I honestly think my chances are looking bleak and USC was never a school I really wanted to go to but needed an insurance anyway. But based on what I want (mentioned above) and assuming I'm accepted to all the remaining 'waiting/applied' schools, which option should I go for? From what I've read I think UCLA might be the best choice (because they make you do an internship + capstone project and have very good network connections) but UCLA's acceptance rate was something like 6.6% for Fall 2020 (Might get rejected from this too ) and UChicago's web page really lacks an substantial professional/career information so idk about them. I've also read/heard things about Columbia's programme that its not as a tight knight community as other schools like MIT MBAn. Any advice for which is best for my professional/career development?

Hi guys. I was wondering if I could get a profile evaluation - what are my chances like for getting into the schools listed below and their respective programs. I was also wondering if I could get some opinions on whether I should submit my GRE scores and will there be any interviews for the schools I am applying to (a simple yes/no in list form for each school will suffice and a couple of words on what the interviews entailed will suffice). So here goes nothing (I feel I'm being a bit too ambitious with my choices and I am also gradually losing my mind over anxiety and stress from this application process hahaha). Thanks for your time, and I'm looking forward to hearing what you all think! Undergrad Institution: Imperial College London, UK GPA: Dean's List Award for Academic Excellence so I think my GPA is something like 3.9 - 4? I am unsure about this because UK doesn't do GPA Undergraduate Degree: MEng Civil and Environmental Engineering (4 Years integrated Masters - I have no Bachelors oddly enough) - Currently in my final year. GRE General Test: Q: 165V: 152 (This score is really low which is why I am asking if I should submit these scores because most schools don't mandate them anymore due to COVID)W: 5.0 * Won't have time to resit my GRE because of commitments to undergraduate program Relevant Courses: Mathematics I & II (We went as far as Fourier Series, Vector Calculus, PDEs, Multivariate Calculus so I'm not sure how much that lines up with American college level Calculus I & II) Statistics Computational Engineering Analysis I, II & III (Programming in MATLAB for Engineering uses - Finite Element Analysis etc.) * MATLAB is a bit of a useless language in industry, which is why I picked up Python and SQL during my internship and I'm quite comfortable with Python right now. Type of Student: International Student (Asian) Programs Applying: Masters in Data Science mostly and Masters in Analytics/Business Analytics Research Experience: By the time of graduation and due to start in January 2021 - Individual Research Project using Machine Learning to assess flood risks by forecasting storm cell movement and intensity in Birmingham, UK. Formally agreed to undertake this project with a supervisor/professor. Extracurriculars: VP of largest national society in my high school Did a 3 week expedition to a rural area in my home country to build a kindergarten in 3 weeks for the villagers and children Represented university in inter-university football/soccer matches and performed in 2 annual events (2018 and 2019) as a dancer Letters of Recommendation: 1x from Internship 2x from academics (1x from high school and 1x from university) Work Experience: AI and Advanced Analytics Intern (3 months) w/ largest Telecommunications company in my home country - Networks team. Used Machine Learning to forecast and identify which cell towers require an upgrade based on cellular throughput, traffic and capacity (not giving much details here because I'm sort of lazy to write everything out). Deals Advisory Intern (2 months) w/ Pricewaterhouse Coopers - Streamlined analysis of receipts and payments transactions with software/programming approach. Participated in liquidation exercise to cross examine and verify authenticity of creditors' claims. Helped assets and divestment team to realise a proportion of company assets during liquidation to stimulate cash flow. My current list: Harvard – Masters in Data Science Stanford - Masters in Statistics, Data Science track UPenn - Masters in Data Science (Early Decision) University of Chicago - Masters in Analytics Brown – Masters in Data Science MIT – Masters in Business Analytics Columbia – Masters in Data Science Duke - MIDS USC - Masters in Applied Data Science I feel that I'm reaching quite high and that I don't stand an optimistic chance of getting accepted into these schools against other applicants because I'm applying straight from undergrad and most people it seems are applying with like 2-3 years of work experience. Should I submit my GRE scores since most schools do not mandate them anymore? Does submitting them regardless pose any benefits to my application over those that do not? Is GPA or GRE score more important? Pointers on how my chances are with these schools and what I should do with my GRE scores are really all I'm looking for! Thanks again!