Most people who end up automating financial markets do not begin there. Aman Chaure certainly did not. He finished his bachelor's in mechanical engineering in 2021 and moved straight into a stable software development role built around automation, systems, and structured problem solving. On paper, it was a logical, orderly career.
Beneath the routine, though, a different curiosity was forming. The market movements of 2020 and 2021 pulled his attention toward finance, not as a spectator, but as someone who wanted to understand the mechanics underneath the price action. The engineer in him could not watch a moving market without asking how it worked, and then asking the question that would reshape his career: could any of this be automated?
What follows is a story less about markets and more about mindset. It is about choosing a path, committing to it fully, and learning that in systematic trading, discipline tends to outlast brilliance.
Why Algo Trading?
Aman's route into trading ran through code, not charts. His day job revolved around automation and systems, so when the markets caught his interest, his instinct was not to watch prices but to interrogate the process behind them. Curiosity quickly narrowed into a single, defining question: what if this could also be automated?
That question led him to algorithmic trading. He started the way many self-taught traders do, experimenting manually and trying to build a feel for the market. It did not take long to reach the limit of that approach. Intuition, he found, was fragile. It worked until it did not, and it gave him nothing he could measure, repeat, or improve. What he needed was structure, a systematic way to approach markets rather than a series of educated guesses.
Why EPAT?
By 2022, that need for structure had hardened into a decision. Aman enrolled in the Executive Programme in Algorithmic Trading (EPAT). For him it was not simply a line to add to a resume; it was a career decision, and he treated it as one.
He had already left his software job before the program began, a choice that says a great deal about how he approached the transition. "I had already left my job because I knew clearly that if I'm working on something else, maybe I won't be able to give it my 100 percent," he recalls. Going all in was not recklessness. It was the same logic he applied to systems, removing the variables that dilute focus and committing fully to the one that matters.
How EPAT Shaped His Approach
EPAT gave him direction in a space that can feel overwhelming to newcomers. Instead of scattered tutorials and conflicting opinions, he now had a structured path that moved through strategy development, backtesting, and risk management in a deliberate sequence.
Just as valuable as what the program taught him was what it taught him to leave out. He learned not only what to do, but what to ignore. For someone entering a field flooded with information, that filter proved to be one of the most useful skills of all. It turned a vague ambition into a workable method, giving him a way to separate signal from noise before a single trade was placed.
Building Something Real
Learning was only the starting point. After completing the program, Aman looked for a collaborator who shared his conviction, someone equally committed to a disciplined, systematic approach rather than a hunch-driven one. He found a teammate with that same vision, and together they set about replacing randomness with structure.
Their strategies were built on logic rather than instinct, focused on areas such as volatility-based trading and momentum. By the end of 2023, the work had produced something concrete. "I had automated a basic portfolio using code written entirely by myself and my teammate," he says. "From that point until today, it's running in a seamless fashion."
That running system became the foundation everything else was built on. It was evidence that the method worked, and a baseline they could measure and improve against. From there, consistency stopped being an aspiration and became a daily practice.
The Real Challenge
The learning phase, it turned out, was the easier part. The real test arrived when live capital entered the equation. "The real challenge actually came when real money got involved," he explains. Drawdowns, uncertainty, and a steady stream of external noise made the day-to-day far more complex than any backtest had suggested.
In those moments, the hardest problem was not the strategy. It was discipline. The temptation to react to every move, to switch systems, to abandon a working process in search of something that felt better, was always present. Aman's response was to lean on process over impulse. "Sticking to the process and not making any abrupt decisions," as he puts it, became his anchor. A system is only as good as a trader's willingness to let it run, and holding that line through both winning and losing stretches is where much conviction is won or lost.
It is worth being clear here. Systematic trading does not remove risk. Drawdowns are part of the process, and no method guarantees a particular outcome. What discipline offers is not certainty but the ability to keep executing a tested process when emotion pushes in the opposite direction.
EPAT and the Role of AI
As the broader technology landscape shifted, particularly with the rise of AI, execution became faster and more efficient. Work that once took days could be compressed into hours, and the operational overhead of running a systematic strategy dropped considerably.
Aman's view of these tools is measured. He treats AI as an accelerant, not an edge in itself. Faster execution and cleaner workflows are useful, but they do not, on their own, produce an advantage in the market. The edge still comes from the quality of the underlying logic and the discipline to apply it, something no tool can supply. In his hands, AI speeds up a process that already works rather than substituting for the thinking behind it.
Looking Ahead
Today, Aman's attention has moved toward refinement. Rather than chasing new strategies, he is focused on improving execution, reducing slippage, and strengthening the overall system. In systematic trading, small inefficiencies compound, and even a strong strategy can be eroded by poor execution, so this attention to detail is where much of the real work now lives.
He frames his journey not as a destination but as an ongoing process of learning and adaptation. Asked what advice he would offer others considering the same path, his answer returns to the theme that has defined his story. "You have to love the process, the adaptation part and the discipline part," he says. In a field where consistency is fragile, that affection for the process may be the most durable edge of all.
Frequently Asked Questions
Do I need a finance background to move into algorithmic trading? No. Aman came from mechanical engineering and a software development role, with no formal finance training. A structured program can help you build the market knowledge you lack, while your existing analytical and problem-solving skills often transfer directly.
Is a programming background necessary? It helps considerably. Aman's coding experience let him build and automate strategies himself rather than depending on others. That said, programming can be learned as part of the journey, and EPAT covers the coding needed to develop and backtest strategies from the ground up.
Should I quit my job to pursue algo trading, the way Aman did? That was a personal decision based on his own circumstances and conviction, not a formula to copy. Many people study alongside a full-time job. The right approach depends on your finances, risk tolerance, and how much time you can commit, so weigh it carefully before making any drastic move.
What does EPAT actually cover? EPAT moves through strategy development, backtesting, and risk management in a structured sequence, along with the programming and quantitative foundations behind them. The value Aman highlights is direction: a clear path through a field that otherwise floods newcomers with scattered information.
How long does it take to build a working automated strategy? It varies widely. Aman completed EPAT in 2022 and had an automated portfolio running by the end of 2023, working alongside a teammate. Building something reliable takes time, testing, and iteration rather than a single breakthrough.
What is the hardest part of systematic trading? For Aman, it was not building strategies but maintaining discipline once real money was involved. Drawdowns and market noise create constant pressure to abandon a working process. Sticking to a tested system through both good and bad stretches is often the real challenge.
Can AI give me a trading edge? AI can make execution faster and workflows more efficient, but Aman is careful to note that tools alone do not create an edge. The advantage still comes from sound logic and the discipline to apply it. Treat AI as an accelerant for a process that already works, not a substitute for it.
Where should a beginner start? Start with the fundamentals of data, strategy logic, and coding for finance before committing real capital. Aman's team focused on areas like volatility-based trading and momentum, but the specific approach matters less than building a structured, testable process and understanding the risks involved.
Next Steps
If you are just getting started with algorithmic trading, begin with the Quantitative Trading Free Learning Track. It includes beginner-friendly courses covering data basics, trading strategies, and coding for finance.
Once you are ready to go deeper, explore Quantra's Algorithmic Trading for Beginners Learning Track, which offers hands-on, application-focused modules to build your skills step by step.
For those looking for a comprehensive, guided journey with mentorship, live lectures, and career support, the Executive Programme in Algorithmic Trading (EPAT) provides a complete foundation for launching or accelerating a career in this field.
Schedule an EPAT counselling call To understand if EPAT is the right choice for you, talk to one of our specialists who have counselled thousands of learners over the past decade and helped them make the right career decision.