Mehul Mehta

Hello Everyone, I am organizing a webinar on Masters in Financial Engineering/ Quant Finance in USA 🇺🇸

I will discuss:

1) Exams & prerequisites required for MFE programs

2) How to shortlist universities and identify the programs that truly matter for quant careers

3) Why students with strong profiles still get rejected from top MFE programs

4) SOP, LOR, Resume, Financial Essay & complete application documentation

5) Visa process, interview preparation, and common mistakes students make

6) Skills universities and recruiters actually expect before joining an MFE

7) Career outcomes, internships, networking, and quant recruiting in the USA

Link for Registration: topmate.io/mehul_mehta_quant/2087591

If you have any doubts please do put in the comment section 😄😄

3 days ago | [YT] | 44

Mehul Mehta

If you have not got an internship this summer, then this post is for you.

Right now, you might be seeing your friends posting internship updates, company badges, office photos, and offer letters.

And somewhere inside, it may feel like:
“Am I falling behind?”

But let me tell you something.

Not getting an internship does NOT mean the end of your career.

I never got an internship during university either.

Yet, I still managed to secure 6 full-time job offers before graduating.

What did I do differently? 😅😅

👉 I started studying topics deeply. Just don’t do ChatGPT instead read 3-4 articles on each topic. Believe me you will be feel ahead just by doing this!

👉 Started building interview guides for each subject and topic so that it can help me when I actually sit for interviews

👉 Worked on quant and risk projects with roommates

👉 Built list of companies that offer quant and risk positions. This list came handy during job search

👉 Spoke to industry folks (via LinkedIn reach) and understood what industry expects from Graduate students

👉 Solved probability questions and brain teaser

Sometimes the student without an internship but with strong skills, projects, communication, and persistence ends up doing much better in the long run.

So if you did not get an internship:

Do not panic.

Do not compare your timeline with others.

Use this summer to build skills that make you undeniable.

A few months of focused effort can completely change your trajectory.

6 days ago | [YT] | 253

Mehul Mehta

Behind every cleared FRM exam, there is usually a story nobody sees.

Not the LinkedIn post.
Not the certificate.
Not the result day celebration.

But this.

Late-night study plans.

Printed schedules full of markings.

Topics crossed out after exhausting workdays.
Weekends sacrificed.

Studying after office hours when the brain is already tired.

For working professionals, preparing for FRM is not just about understanding risk management.

It is about consistency.

You come back from work after spending 8–10 hours in meetings, coding, modeling, reporting, validation, or dealing with production issues……and then still open probability, VaR, derivatives, fixed income, or credit risk notes.

Some days you study for 5 hours.

Some days you can barely study for 20 minutes.

Some days motivation disappears completely.

But you still continue.

That is what makes these professional exams difficult.

Not only the syllabus.

But managing life, work, stress, and preparation together.

To everyone preparing for FRM, CFA, CQF, MFE interviews, or quant roles while working full-time:

Respect your own journey.
Progress does not always look perfect.

Sometimes it looks like a crumpled study sheet filled with ticks, notes, unfinished chapters, and coffee stains.

And that is perfectly fine.

#Discipline

1 week ago | [YT] | 85

Mehul Mehta

What I’m slowly learning in Quant…

After ~7+ years in derivatives, fixed income, and risk, a few things are becoming clearer:

a) Models are useful, but fragile
Black-Scholes, GARCH, copulas — they all work… until they don’t.
Every model is just a structured assumption about reality.

b) Data quality > model complexity
A simple model with clean data will outperform a complex model with noisy inputs — almost always.

c) Risk is nonlinear (and unforgiving)
Delta works… until Gamma shows up.
Variance works… until tails dominate.
Most real losses come from what wasn’t modeled.

d) Validation is not a formality
Model validation teams aren’t blockers — they’re your last line of defense.
The best quants build with validation in mind.

e) Markets don’t care about elegance
You can have the most mathematically beautiful model…
but if it doesn’t capture P&L under stress, it’s useless.

f) Experience compounds faster than theory
You understand convexity better after seeing losses than after reading formulas.

g) Simplicity scales
The models that survive in production are usually the ones people can explain, debug, and trust.

Still learning.

Still getting things wrong.

But slowly getting better at asking the right questions.

PS: This post contains my views and doesn’t relates to views of my company.

2 weeks ago | [YT] | 100

Mehul Mehta

Most students want to enter Quant Finance because of the high salaries.

But here’s a question worth asking yourself:

If the same job paid a low salary, would you still be interested in it?

It’s an uncomfortable question, but an important one.

Because if the honest answer is no, then you might be chasing the outcome, not the craft.

And in fields like quant finance, chasing outcomes rarely works in the long run.

Quant finance is not just about compensation.

At its core, it is about:
👉 curiosity for mathematics and statistics
👉 building models to understand uncertainty
👉 thinking deeply about risk and probabilities
👉 working with messy real-world data
👉 continuously learning new tools, methods, and ideas

The people who thrive in this field are usually the ones who genuinely enjoy the process of solving difficult problems.

Not just the paycheck at the end of the month.

Another reality that many students don’t talk about enough:

Careers rarely start at their peak.

Many professionals in quant, finance, tech, and research started with:
👉 modest salaries
👉 junior roles
👉 long learning curves
👉 and plenty of mistakes

And that’s perfectly normal.

There is no shame in starting small early in your career if you are learning the right things.

In fact, the early years should ideally be focused on learning and skill building, not maximizing salary.

Because over time something powerful happens:

Skills compound.

If you spend the first few years focusing on:
• strong foundations in statistics, probability, and programming
• real problem-solving experience
• understanding markets and risk
• building projects and models
• learning how to think critically

then opportunities tend to follow.

The people who become valuable in this field are not necessarily the ones who started with the highest salaries.

They are the ones who became exceptionally good at what they do.

Money often follows people who build rare and valuable skills.

Not the other way around.

So if you are entering quant finance, ask yourself:

Do I enjoy the learning process even when it’s difficult?

Do I like thinking about models, data, and uncertainty?

If the answer is yes, then you are on the right path.

And if the salary is small at the beginning, that’s okay.

Because careers are long, and compounding works in skills just like it works in
finance.

#QuantFinance #CareerAdvice #Students #FinanceCareers #Learning #LongTermThinking

1 month ago | [YT] | 62

Mehul Mehta

Everyone talks about the importance of staying loyal to one firm for a long time.

And yes, stability has its value.

But there is something people often ignore.

Staying in the same role for 10 years while doing the same thing repeatedly, without learning anything new, can be far more damaging to a career.

Early in your career, the most valuable thing is not the number of years you spend at a company.

It is how much you grow during those years.

Over time, changing firms allowed me to work on a wide range of problems and expand my understanding of quantitative finance.

Through different roles and projects, I have had the opportunity to learn and work on areas such as:

• Fixed Income analytics
• Equity Derivatives
• Time Series Modeling
• Stochastic Volatility Models
• Stochastic Interest Rate Models
• Building end-to-end automation frameworks

Each transition came with new challenges, new systems, new teams, and most importantly, new learning curves.

And that learning compounds over time.

Changing firms should not be about chasing titles or switching for the sake of switching.

It should be about finding environments where you can continue to grow, build, and expand your skill set.

Because at the end of the day, a career is not defined by how long you stayed somewhere.

It is defined by how much you learned along the way.

#QuantFinance #CareerGrowth #Learning #FinanceCareers #ProfessionalDevelopment

1 month ago | [YT] | 35

Mehul Mehta

A few years ago, I had absolutely no idea what quantitative finance really meant.

Terms like stochastic processes, volatility modeling, and derivatives pricing sounded extremely intimidating.

The formulas looked complex, and honestly, the whole field felt difficult to even approach.

But curiosity kept pushing me.

I started reading more about financial markets, experimenting with different models, and trying to understand how mathematics is used to explain market behavior.

At first, many things didn’t make sense.

But over time, concepts slowly started becoming clearer.

What fascinated me the most was realizing that financial markets, which often look chaotic and unpredictable, can actually be studied through mathematical frameworks.

Models may not perfectly predict the future, but they help us understand risk, uncertainty, and market dynamics much better.

Looking back, the most important thing in this journey wasn’t knowing everything from the beginning.

It was simply staying curious long enough to keep exploring.

And the interesting part about this field is that the learning never really stops.

Still learning.

Still exploring.

#QuantFinance #Derivatives #Volatility

2 months ago | [YT] | 115

Mehul Mehta

The world is changing faster than most people realize.

Bloomberg just introduced ASKB, bringing agentic AI directly into the Bloomberg Terminal.

This is not just a chatbot upgrade.

This is AI embedded into core investment workflows, capable of pulling data, research, analytics, and generating structured insights in real time.

This signals something bigger.

Agentic AI is moving from experimentation to production across financial institutions.

Firms like BlackRock are integrating AI into portfolio construction and risk systems.

JPMorganChase is deploying AI internally across research and trading workflows.

Even major exchanges and data providers are embedding AI directly into analytics infrastructure.

We are entering a phase where AI does not just assist.

It monitors, reasons, and acts within financial systems.

In investment, trading, and risk management, this will fundamentally change how decisions are made.

The question is no longer whether AI will be adopted.

The question is how fast institutions adapt.

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2 months ago | [YT] | 31

Mehul Mehta

This is my third company in the US.

Every time I switched job I had a different strategy in mind.

During my master’s, I was an international student and I had just one goal.

Get a job in the US, no matter what.

So I followed the law of large numbers strategy.

I applied to nearly 2,000 roles and eventually received multiple offers.

My first role in the US was at Regions Bank.

This is where I got my first breakthrough in the USA job market.

The work at Regions was great, but I wanted to move towards market facing modeling roles.

So I started looking jobs which are closer to the markets.

After 1.5 months of searching, I received three offers and chose Charles Schwab, where I worked in Fixed Income Quant for two years.

I feel I had the best time at Charles Schwab as I had exponential learning curve.

Working there, I discovered my real inclination: Derivative pricing and stochastic modeling.

So, I started looking for the next role and my strategy changed again.

No mass applications.

Only a fixed number of highly focused applications.

And once again, I received 3 offers.

Here is the biggest lesson.

Career advice is never universal.

Some seniors will tell you to apply everywhere.

Others will say apply selectively.

Both can be right.

Because the correct strategy depends on your stage of life.

If you are an international student in the US, your first priority is simple.

Get a job in the system.

You can optimize later.

You can specialize later.

You can move closer to your dream role later.

But first, survive, stabilize, and enter the market.

Everything else follows from there.

2 months ago | [YT] | 149

Mehul Mehta

Happy to share that I’ve passed the FRM Level 1 exam 😄😄

This journey involved solving 1000+ practice questions, revisiting concepts multiple times, and truly understanding the intuition behind risk models rather than memorizing formulas.

FRM Level 1 is a strong foundation, but this is just the beginning. 💪💪

Looking forward to Level 2

4 months ago | [YT] | 154