- Joined
- 8/20/22

- Messages
- 12

- Points
- 3

B.Sc in Computer Science with Data Analytics ( NAAC A accredited, top 20 in NIRF ranking in India) - Recent grad

Undergrad Coursework:

Statistics and Probability, Applied Statistics, Optimization techniques, Graph Theory, Linear algebra, Matrix Algebra, Predictive Analytics

Python, R, C++, Machine Learning, Artificial Intelligence, Parallel Computing, Data Mining.

GPA 8.8/10, I have perfect scores in Statistics and Probability, Optimization Techniques

I realized my courses didn't have calculus so used MIT OCW to learn Single Variable Calculus and Stochastic Processes.

I have won a couple of international hackathons in Quantum Computing and Fintech ( hosted by Stanford & Yale, FIU, UCBerkeley, NYU AbuDhabi, McMaster)

Have an internship in Portfolio Optimisation using QC.

Working as a full-time (remote) Dev and ML engineer at a Startup in California. The area of work is mostly around Parallelization, NLP, Backend, and Query Optimisation.

Final Year Project: Stock screener using fundamental analysis. I am also soon starting as an intern at a local investment analytics firm as an analyst

I manage a small portfolio for my family members and I found it quite interesting, Portfolio management is something I want to do in a long term.

I am planning to Do an MS in Quantitative Finance or Computational Finance in the US.

Looking at the other profiles I see that my UG coursework lacks math, so should I do an MSc in Statistics in India before I go for MS?

Please advice.