Computer Science to Quantitative Finance: Tushar's Algo Trading journey

3 min read

Algorithmic trading is a great career option for people who are interested in engineering, mathematics, statistics, and finance. It's very intellectually stimulating and can be financially rewarding, as well.

Tushar is a quantitative developer. He has built low-latency quantitative trading systems. He is proficient in C++, Python, C, JavaScript, and SQL. As a proud EPATian, Tushar is using everything he has learnt through EPAT to move forward in his career in quantitative finance.

We caught up with Tushar over a call and the following is his success story!

Hi Tushar, tell us about yourself!

Hi! I’m Tushar Chawla. I'm based in the US. I currently work in Dubai, and I’ll be heading back to the US for a master's degree soon. I’m working as a Senior Quantitative Software Engineer at iBloxx capital.

I research trading strategies, backtest them, and build systems to deploy them in live markets. Until now, our team have mostly used Python for this.

I graduated from the University of Michigan in 2020 with a Bachelors in Computer Science.

The COVID situation isn’t as bad here as it is in many parts of the world right now. Most of the people here are vaccinated and the number of COVID cases is dropping every day. I'm used to wearing masks everywhere now.

How did you go from Computer Science to Algo Trading?

I started off at college as a business student. I originally planned to get into discretionary trading or investment banking. However, I took a computer science course during my first year at Michigan and became interested in technology as well.

I decided to focus on learning computer science first. I decided to combine both my passions together, after graduating, through algorithmic trading. I started my own fund after graduating, which didn't work out due to a lack of experience and funding.

After college, I was looking for a way to learn about quantitative/algorithmic trading and I stumbled across EPAT on Google. It seemed like the best course on the internet for the subject, and I spent a part of four months taking this course while operating my fund before I got an opportunity to work for a larger fund in Dubai.

QuantInsti is a great resource to use for algorithmic traders. Even at work in Dubai, when I was required to summarize order book data into OHLC data, I used a QuantInsti blog article for reference.

Why did you choose EPAT over any other course?

Most algorithmic trading courses on the internet weren’t technical enough, and the others were about quantitative finance and didn’t cover algorithmic trading in-depth.

EPAT was the only course that I could find online that seemed to have a proper technical focus on algorithmic trading. It seemed to have a great support system behind it as well, which I can confirm. EPAT has some great success stories, and I confirmed their validity by contacting a few of the people mentioned on the QuantInsti website.

I learned a lot about market microstructure, building backtesting programs, and trading strategies such as arbitrage and mean reversion through EPAT. I liked the lectures, the content, and the structure of the course.

What’s the best feature of EPAT that really stood out for you?

I really liked the placement services of EPAT, through which I got my job in Dubai. I got this opportunity through a direct apply link, which the placement cell had sent me.

The EPAT Placement cell tries its best to connect you with job opportunities in the domain, in different countries. One of my co-workers also got the same job through QuantInsti. His name is Jonathan Moreno and he’s also an EPAT alumnus.

Your advice for the individuals who wish to pursue algo trading

Firstly, you should decide which role you would like to take up in quantitative finance based on your experience and skillset. Even though it's a niche domain, it has a lot of different roles such as risk management, pricing, quantitative research, quantitative trading, and quantitative development.

You don't really need a master’s degree to get into the field, but it might help. If you're new to the field, one good way to learn more would just be to learn the basics of quantitative finance or algorithmic trading through a course like EPAT and then try to build your own trading track record at the retail level.

Algorithmic Trading is a great career option for people who are interested in computer science, mathematics, statistics, and finance. It's very intellectually stimulating and financially rewarding as well if you’re good at it.

Your focus on building your skills and applying them to further your career goals is truly commendable. We wish you the best of luck in your future endeavours and we’re looking forward to your contribution to the quantitative finance world.

If you too desire to equip yourself with lifelong skills which will always help you in upgrading your trading strategies. With topics such as Statistics & Econometrics, Financial Computing & Technology, Machine Learning, this algo trading course ensures that you are proficient in every skill required to excel in the field of trading. Check out EPAT now!

Disclaimer: In order to assist individuals who are considering pursuing a career in algorithmic and quantitative trading, this success story has been collated based on the personal experiences of a student or alumni from QuantInsti’s EPAT programme. Success stories are for illustrative purposes only and are not meant to be used for investment purposes. The results achieved post completion of the EPAT programme may not be uniform for all individuals.

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