Realistic to get into quant with my background?

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Hi everyone,

I'm a 19M from Mumbai, currently pursuing a Bachelor of Financial Markets (BFM). Alongside my degree, I'm also pursuing Actuarial Science.

From what I've studied so far, I've noticed that many actuarial subjects seem to overlap with quantitative finance:

* CS1:Probability theory, statistical inference, regression, Bayesian statistics, GLMs, Monte Carlo simulation, etc.

* CM2: Brownian motion, Itô processes, option pricing, interest rate modelling, and other stochastic calculus concepts.

* CS2: Stochastic processes (Markov chains and Markov jump processes), machine learning,time series analysis, extreme value theory, survival models, etc.

I'm also pursuing the **FRM** alongside these, if that's relevant.

My questions are:

1. Given this quantitative background, is it realistic to break into quant finance by self-learning the remaining gaps (primarily **linear algebra, programming (Python/C++), data structures & algorithms**, and relevant ML topics) through online resources?

2. Or is an **MFE/MQF** (or perhaps a Master's in Machine Learning/Statistics/Applied Mathematics) practically necessary to become a quant?

3. Or am I at a significant disadvantage because I'm from a commerce background (BFM) rather than engineering, mathematics, physics, or CS? Do firms mostly hire IITians/top engineering graduates, making this path unrealistic?

I'd really appreciate honest opinions from people working in quant roles or those who've gone through the hiring process. Thanks!