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

23 hours ago | [YT] | 23

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

4 weeks 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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1 month 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.

1 month ago | [YT] | 147

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

1 month ago | [YT] | 154

Mehul Mehta

Quant Firms in India 🇮🇳

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3 months ago | [YT] | 266

Mehul Mehta

Algorithmic Trading: The world where mathematics meets markets

Most people think algo trading is only about writing a “fast code.”

In reality, it is a combination of statistics, market microstructure, execution science, and risk management.

Here is how I explain it in one line

Algo Trading is using rules, data and automation to execute trades faster and more efficiently than humans.

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3 months ago | [YT] | 80

Mehul Mehta

Quant Roles explained 💯

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4 months ago | [YT] | 146

Mehul Mehta

Over the years I’ve worked with some of the best Quants in the industry. 💯

What makes them stand out are not just models and math, but the habits they live by:

1. Discipline like traders — structured days, focused routines

2. Attention to detail — checking data twice, assumptions thrice

3. Curiosity beyond finance — physics, CS, probability, even philosophy

4. Reading research daily — they stay ahead by learning continuously

5. Coding relentlessly — always building, testing, automating

6. Questioning everything — never taking inputs or outputs at face value

7. Explaining simply — breaking down complex math into clear insights

8. Staying calm under pressure — markets move fast, but they stay grounded

9. Networking with purpose — exchanging ideas with academics, traders, and engineers

10. Balance of speed & depth — quick to act, deep when solving problems

At the end of the day — habits build great Quants, not just equations.

7 months ago | [YT] | 91

Mehul Mehta

Stochastic Modeling 😂😂

7 months ago | [YT] | 52