SQL
SeqLL Inc. Common stock
stock NASDAQ

The software engineering interview at QRT typically kicks off with an online assessment or an initial technical screen, followed by two or three live coding rounds and a final team chat. You actually need both algorithmic practice and deep language knowledge, not just one or the other. Expect medium level data structures and algorithms questions covering arrays, trees, or dynamic programming, but be prepared for direct questions on language mechanics. If your background is in C++ or Python, they will probe you on memory management, object oriented principles, threading, garbage collection, and operating system basics.

For your preparation before hearing back from the recruiter, assume at least a mid level bar, since junior and senior tracks mostly differ in system design depth rather than core coding standards. When the recruiter follows up, ask specifically about the target team, because data platform roles will emphasize distributed pipelines, SQL, and data processing, whereas core execution roles lean heavily into low latency and networking. To help candidates handle tough live technical grilling, my team created an [interviews.chat](http://interviews.chat) that gives candidates the edge to secure top tier compensation packages in quant finance.

**BCA graduate trying to build a career in Quant looking for advice/opportunities**
Hi everyone,
I'm a 2024 BCA graduate from India and I'm currently pursuing an MCA. I'm trying to figure out the best way to move forward in quantitative finance/trading and would appreciate advice from people already working in the field.
I have a little over a year of combined professional experience across a trading startup and a stock broking firm.
My work has mainly involved Python, market data, backtesting and quantitative research infrastructure. Some of the things I've worked on include:
* Building Python pipelines for historical NSE/BSE futures & options data
* Developing and backtesting systematic options strategies
* Building portfolio/momentum backtesting systems
* Walk-forward testing and performance analytics (Sharpe, drawdown, CAGR, equity curves, etc.)
* Data engineering using Python, Pandas, SQL and ClickHouse
* AWS, Git and related development tools
I left the broking firm in January 2026. Since then, I've been trading BTC derivatives manually with a small amount of my own capital while building Python tools/analytics around my trading.
I'm also maintaining my trading history so that over time I have an actual track record rather than just claiming that I trade. The capital is currently small, so I'm treating this primarily as a way to develop and test my understanding of markets and risk with real money.
My long-term goal is to work deeper in the **quantitative trading/research space** rather than move into generic software development.
I'm trying to understand what my most realistic next step should be.
Should I target Quant Developer / Quant Research / Systematic Trading / Trading Analyst roles? Are smaller prop firms, trading desks or startups more realistic given my BCA + MCA background?
I'm also aware that traditional quant roles can be very math-heavy and often recruit from IITs/top universities or master's programs in mathematics/statistics/CS. I'd especially appreciate advice from anyone who entered the field through a less traditional route.
If anyone here works at a prop shop, trading firm, brokerage, hedge fund, fintech or quant startup and thinks my background could fit something you're working on, I'd also be happy to connect.
I'm not looking for someone to fund my personal trading. I'm primarily looking for **career advice, opportunities, and feedback on what skills I should build next.**
Thanks.

The software engineering interview at QRT typically kicks off with an online assessment or an initial technical screen, followed by two or three live coding rounds and a final team chat. You actually need both algorithmic practice and deep language knowledge, not just one or the other. Expect medium level data structures and algorithms questions covering arrays, trees, or dynamic programming, but be prepared for direct questions on language mechanics. If your background is in C++ or Python, they will probe you on memory management, object oriented principles, threading, garbage collection, and operating system basics.

For your preparation before hearing back from the recruiter, assume at least a mid level bar, since junior and senior tracks mostly differ in system design depth rather than core coding standards. When the recruiter follows up, ask specifically about the target team, because data platform roles will emphasize distributed pipelines, SQL, and data processing, whereas core execution roles lean heavily into low latency and networking. To help candidates handle tough live technical grilling, my team created an [interviews.chat](http://interviews.chat) that gives candidates the edge to secure top tier compensation packages in quant finance.

**BCA graduate trying to build a career in Quant looking for advice/opportunities**
Hi everyone,
I'm a 2024 BCA graduate from India and I'm currently pursuing an MCA. I'm trying to figure out the best way to move forward in quantitative finance/trading and would appreciate advice from people already working in the field.
I have a little over a year of combined professional experience across a trading startup and a stock broking firm.
My work has mainly involved Python, market data, backtesting and quantitative research infrastructure. Some of the things I've worked on include:
* Building Python pipelines for historical NSE/BSE futures & options data
* Developing and backtesting systematic options strategies
* Building portfolio/momentum backtesting systems
* Walk-forward testing and performance analytics (Sharpe, drawdown, CAGR, equity curves, etc.)
* Data engineering using Python, Pandas, SQL and ClickHouse
* AWS, Git and related development tools
I left the broking firm in January 2026. Since then, I've been trading BTC derivatives manually with a small amount of my own capital while building Python tools/analytics around my trading.
I'm also maintaining my trading history so that over time I have an actual track record rather than just claiming that I trade. The capital is currently small, so I'm treating this primarily as a way to develop and test my understanding of markets and risk with real money.
My long-term goal is to work deeper in the **quantitative trading/research space** rather than move into generic software development.
I'm trying to understand what my most realistic next step should be.
Should I target Quant Developer / Quant Research / Systematic Trading / Trading Analyst roles? Are smaller prop firms, trading desks or startups more realistic given my BCA + MCA background?
I'm also aware that traditional quant roles can be very math-heavy and often recruit from IITs/top universities or master's programs in mathematics/statistics/CS. I'd especially appreciate advice from anyone who entered the field through a less traditional route.
If anyone here works at a prop shop, trading firm, brokerage, hedge fund, fintech or quant startup and thinks my background could fit something you're working on, I'd also be happy to connect.
I'm not looking for someone to fund my personal trading. I'm primarily looking for **career advice, opportunities, and feedback on what skills I should build next.**
Thanks.