Making a Career in Algorithmic Trading

15 min read

By Viraj Bhagat

The advent of algorithmic trading in the late last century caused a massive “techtonic shift” in the way trading took place in exchanges worldwide. This is a perfect source if you wish to make a career in Algorithmic Trading. Here, we highlight some important factors for job seekers in the domains of High Frequency Trading, Automated Trading, Quantitative Trading or simply Quant Jobs.

Even though you may have a different profile, educational background or work experience, it is possible for one to be an Algorithmic Trader with some essential knowledge of the domain. It is about time everyone realized the true potential of algorithmic trading.

We'll cover:


Jobs and Career in Algorithmic Trading

The last couple of decades have seen an exponential growth in the algorithmic trading market and it continues to grow at a significant pace.

According to the report published by Allied Market Research, the global algorithmic trading market garnered $12.14 billion in 2020, and is expected to garner $31.49 billion by 2028, manifesting a CAGR of 12.7% from 2021 to 2028.

Today, algorithmic trading and high-frequency trading are recognized by companies and exchanges all over the world and have become the most common way of trading in the developed markets. Be it trading in stocks, derivatives, Forex or commodities, trading firms worldwide adopted algorithmic trading in a big way.

Big banks, hedge funds, and other trading firms are now hiring the best talent to stay ahead of their competition and to gain big bucks leading to a surge in algorithmic trading jobs.

Students, engineering graduates, developers and even old-school traders are aspiring to build a career in algorithmic trading. As per Bloomberg, Citibank hired 2500 programmers for the unit that houses its traders and investment bankers, bulking up on coders and data scientists as technology reshapes the business.

Developers from non-technical backgrounds (like telecom industries or verticals which focus heavily on programming) are in demand. Why? They’ve spent years within the same industry they have enough relevant knowledge about the basics and the nuances of programming which are essential to Trading.


Types of Quants

People frequently enquire and are curious to learn about various online trading jobs, algorithmic trading jobs, futures trader jobs, etc. in their journey of an algorithmic trading career.

Here we list down a few profiles to understand what types of roles are available in the industry and what type of skills would be required to take them up.

  • Desk Quant - Implement pricing models that are directly used by traders
  • Model Validation Quant - Implement pricing models to validate Front Office models
  • Front Office Quants (FOQs) - Develop and manage models for calculating the price of assets on the markets
  • Investment/Asset Management Quants - Develop models for mitigation of losses in investments
  • Research Quant - Research and create new approaches for pricing
  • Quant Developer - A developer/programmer from the field of finance
  • Statistical Arbitrage Quant - Identify data patterns and suggest automated trades based on the findings
  • Capital Quant - Model the bank’s credit exposures and capital requirements

These are some of the roles which prevail in the market among the various other types. Developers are also sought after in the domain of High-Frequency Trading (HFT Trading).


Who Employs Quants?

Some of the questions asked for employment in Algorithmic Trading domain are:

  • Who will hire Algorithmic Trading professionals?
  • Who will give jobs to Quants?
  • What companies hire Quants?

List of companies that hire Quants

Here's a list of some famous companies that employ Quants:

  • Commercial Banks that hire Quants
    • RBS
    • HSBC
  • Investment Banks that hire Quants
    • Citibank
    • Goldman Sachs
    • Lehman Brothers
  • Hedge Funds that hire Quants
    • The Citadel Group
  • Accountancy Firms[3] that hire Quants
  • Software Companies that hire Quants
  • Finance Firms that hire Quants

What Do Recruiters Look for in a Resume?

Recruiters are always on the lookout to hire the most talented and skilled individuals out there for their organisations. But when hiring for the domain of algorithmic trading:

  • What do recruiters look out for?
  • What describes an algorithmic trader job description or a quantitative analyst job description?
  • What type of job will help one’s algorithmic trading career?

Algo Trading job requirements

Following are some requirements from established companies in the Algo Trading domain, for selection of candidates that they look out for:

  • For the position of Trading Strategy Development, the knowledge of Python & R would be an advantage.
  • To become a Python Developer an advanced skill-set in programming languages like Python is largely preferred
  • A domain knowledge in stock markets (quant, fundamental, technical, derivatives, macro, etc.) and strong Logical skills are valued
  • Those with Master’s in Applied mathematics or statistics, MBA from IIM, B.Tech computer science can become Quantitative Researchers and Traders with the ability of successful implementation of profitable trading strategies (from ideation to execution i.e. research, design, back-test and execution) as well as knowledge and experience of working with data analytical tools like R, Python, etc.

Tips for Algo Trading job interviews

Mentioning these qualities while being thorough with them would increase your chances of being selected by them. There are people who have become successful traders although being from a commodity background, being Finance & Tech Grads, being Technocrats and Engineers, etc.

One should be able to demonstrate a strong understanding of the core areas that are highlighted in their resume. Don’t mention skills you don’t have, or have only a partial or basic knowledge of - that would leave a negative comment. Not to forget the basic rule ie. being honest about your profile and skills.

Recruiters also tend to give positive weight if the candidate has undertaken a project work or published any research papers in his/her areas of interests.


Salaries for a Career in Algo Trading

One of the most commonly asked questions is: How much do algorithmic traders make?

There exist a variety of roles for multiple businesses and companies, depending on the type of knowledge and skills you possess. QuantInsti’s career cell shares these numbers on the QuantInsti website, stating job opportunities & salary packages bagged by the participants of their algo trading course.

Algo Trading salaries

  • Data Scientist: INR 1.5 million per annum
  • Algo Trader: INR 800,000 per annum + incentives,
  • HFT trader: up to INR 2 million per annum,
  • Quant Research Analyst: INR 2 million per annum,
  • Quantitative Research: AED 1,00,000 + up to 40 % incentives per annum,
  • Trader: SGD 120,000 + performance linked bonus per annum,
  • Trader Derivatives: HKD 384,000 per annum + performance linked bonus

It is a known fact that salaries & bonuses are lucrative in algorithmic trading firms.

Variation in Algo Trading jobs and salaries

They vary:

  • with different job roles and cadres
  • with companies where bonuses get equally split between traders and programmers based on the profitability of a strategy
  • with the type of the trading firms (e.g. Family office, or bank, or High Frequency Trading (HFT) firm etc.) and
  • the strategies (low-frequency trading strategy / high-frequency trading strategy) that are deployed by the firms

Salaries are based on the posts or designations for which one is hired. Salaries for the following and other posts would be as per the hierarchy of that respective company.

This results in different types of roles and jobs in the Quant or Algorithmic trading space. Equities market also offers a broad range of career opportunities.

Check out this article to learn specifically about the salaries in the industry.


Skills Required for a Career in Algo Trading

Be Future Ready. Skills Matter.

A quant designs and implements mathematical models for the pricing of derivatives, assessment of risk, or predicting market movements.

Following are the most important and relevant skills that one would be required to have to progress in the domain of Algorithmic Trading and will prove to be essential in one’s algorithmic trading career path:

Analytical skills

Having an analytical bent of mind is a very important quality for any quant trader/developer, and is valued in an interview.

For example, an interviewing candidate may be given a huge data set and asked to find patterns from the data. Candidates get evaluated on how they approach any given problem and their ability to justify their solutions objectively.

Mathematical skills

As the core of algorithmic trading revolves around algorithms, data, and programming, having reasonable programming skills and a basic understanding of statistics and calculus is important for any job seeker in algo/HFT trading.

For example, if a candidate is applying to a firm that deploys low latency strategies, then an expert level of programming would be expected from such a candidate.

Programming skills

Knowledge of a programming language is an added advantage as it enables you to function independently. Traders are inclining towards learning long-term effects and benefits of Coding especially Python.

Python is good for conceptualizing, backtesting of strategies, and has many libraries for validation and visualization of results. It can also be used by firms for strategies that are not dependent on low latency. On the other hand, C++ is usually used by firms that trade very low latency strategies.

Thus, if the objective of an aspiring developer is to get into an HFT firm, then irrespective of the language that he starts with, he will have to finally end up learning C++.

The strategy development process

While devising any strategy, it is important to understand the risks and rewards associated with that strategy in order to determine whether it has an edge in the markets. This is done during the backtesting of a strategy.

The frequency of trading, instruments traded, leverage also needs to be taken into consideration before going live with the strategy in the markets.

A single strategy doesn’t guarantee profits year-after-year. One has to formulate and overhaul strategies regularly basis using advanced mathematical models & statistics to remain profitable in the markets.

To understand various algorithmic trading strategies, you can learn about the algorithmic trading strategies, paradigms and modelling ideas.

Understanding the Financial Markets

Quantitative trading involves dealing with large datasets, trading in different instruments like stocks, derivatives, Forex etc. Hence, even if you are coming from a non-finance technology background, as a developer in a quant firm, you need to have a fair understanding of the financial markets.

Trading firms usually make their new recruits spend time on different desks (e.g. quant desk, trading, risk management desk) to gain an understanding of the markets.

Besides these, it is necessary that one is equipped with the domain knowledge. To know more on skill sets required, check out this infographic about the top skills for nailing a Quant or Trader interview.

If one is thorough with these points, they need not ask questions like: What are the skill sets required to become an Algo trader?

Besides these, one could also develop the following skills:

  • Quantitative analysis
  • Programming skills
  • Statistics and Probability
  • Knowledge of financial markets and trading
  • Logic and reasoning
  • Econometrics
skills for quants
Skills for Quants

Impact of Ml and AI on Your Algorithmic Trading Career

ai in finance
(Source: Business Insider) AI In Finance

Business Insider goes on to state:

With the aggregate potential cost savings for banks from AI applications estimated at $447 billion by 2023, banks are finding new ways to incorporate the tech into their services.

While some of the larger trading houses like Blackrock, Two Sigma, Renaissance technologies and others are employing Artificial Intelligence for picking stocks, JP Morgan and IBM are trying to bring AI into financial regulations and compliance.

In fact, there are hedge funds that are purely based on AI, namely Rebellion Research and KFL Capital. People are moving to carve their own artificial intelligence career path based on their Trading skills.

Companies have begun tapping into newer technologies like AI to harness their power and to rush ahead with technology. And for this, they require individuals with the right set of skills that would help them get ahead in this race. Coding has turned out to be the #1 skill in this era of automation.


Learn and Upgrade to Establish Your Career in Algo Trading

It is simple. Just keep learning. With the right set of skills, you can enter the role of your bidding in your algorithmic trading career. It is necessary that one opts for only the best skills to keep growing and staying ahead in their game.

  • An interest in building models could help you become a Quant Analyst / Model Developer
  • Coding, maintaining, or modifying strategies could make you a Strategy Developer, or lead you to Core Development work
  • Finance and problem-solving abilities could make you a better Trader
  • Knowledge of strategies, market microstructure and programming could help you land jobs with Banks and Brokerage Houses
  • Arbitrage and Quantitative Strategies can help you cement a Quant Analyst or a Quant Developer job in top firms

These are among a variety of widespread scenarios which will help you get just the job that you are capable of doing. It is essential for you to identify the skills required to move ahead.

However, identifying key fields like Artificial Intelligence, Big Data, Python, etc. and building related skills would have a great impact on how your career shapes. Here’s a step-by-step guide to learn more about it.

Check out this inspiring story of Raj who despite being in the technical space for over twenty years, became an independent Algorithmic Trader.


Useful Resources to Boost Your Career in Algo Trading


FAQs About a Career in Algorithmic Trading

Here are some of the most commonly asked questions which we came across during our Ask Me Anything session on Algorithmic Trading.


Question: How can a finance guy make a career in this domain?

Reply: As I said, it is a set of three things i.e. statistics & econometrics, programming (which is financial computing) and quantitative trading strategies. So if you have a finance background and you are already good at the 1st and 3rd aspect then you need to pick on the financial computing side.

If someone tells you that you are already a trader and you do not need to learn to programme to automate your strategies, they might not be lying, you can do that.

There are some tools available with the ‘drag-and-drop’ option where you can build a logic without actually coding. But, these functions are limited and it will also limit your ability to change or modify your strategy or implement your ideas.

So it really helps if you know of the algo trading programme. Even if you are not trading, if you are doing data analysis it will help you a lot. The things you can do with two lines in a python code, you will need a lot more if you are doing it on a non-programmable tool.


Question: What are the skills required to land a job as an Algorithmic Trader?

Reply: The kind of skills that you would need typically would revolve around ‘the three pillar’ of algorithmic trading (like explained before).

If you are looking:

  • to become a trader yourself, then you would need to learn all the three domains
  • to become an algorithmic developer, then you would need more expertise on the programming side
  • to become more of a strategist, in that case, you would need deeper understanding of the trading strategies (like derivatives, all different type of classes etc.)
  • become a quant analyst, then you need to have a stronger expertise in statistics and econometrics

So everyone would need to know all these three but how much expertise you would need to know in each one of them that varies depending upon what kind of profile you are targeting.


Question: What are the career opportunities in Algorithmic Trading? How can EPAT help?

Reply: Besides the three aspects mentioned above - including quant analyst, traders and developer there is a list of profile out there. This varies from:

  • back-office roles,
  • front office roles,
  • analyst roles,
  • development roles,
  • management roles,
  • network management and much more.

Algorithmic trading is one of the more rewarding streams compared to conventional trading or other career domains and it is much more intellectually stimulating as well.

If you want to do something where you want to contribute and experiment a lot these kinds of profiles can really help.

QuantInsti's EPAT course has a dedicated placement and career cell that helps you find the right connections and acquire the right information. IT helps:

  • in getting you placed,
  • seeking guidance to move up the ladder in your organization in the same or a different role,
  • to start a new business,
  • if you need a broker connection, vendor connection,
  • funds,
  • investments, etc.

So that’s where QuantInsti’s career cell becomes much more instrumental. They keep on bringing you different opportunities available in the market in different geographies.


Question: What prospects can someone with 10-20 years of domain expertise and no trading experience expect as an algorithmic trader?

Reply: We do have an interesting case study which is about an EPAT alumnus in his 40s. He was not from a trading background but he was able to make a switch that to after 20+ years of experience.

So yes, such opportunities do exist. He did put in a lot of time, effort and commitment. If these things are there then yes there are a lot of opportunities, opportunities that keep on coming, we share such opportunities with all our participants every week but ultimately it’s you.

We can only guide, you have to go and win the war.


Question: Just how liquid is the job market for someone who has completed QuantInsti’s executive programme?
Or Are jobs in quant trading the reserve of PhDs?

Reply: A PhD definitely helps but not all the firms need just PhDs. You need to know your stuff that’s what the key requirement we keep on seeing from different placement partners and not just in particular geography but everywhere.

HFT firms keep a focus of hiring lot of maths and physics PhD guys but not a huge lot of them so it’s an advantage but not like you cannot get into quant trading without a PhD.


Question: Most of the quant interviews check the problem-solving skills of the candidate through puzzles etc.
How is EPAT going to prepare me for such interviews?
Does QuantInsti have HFT firms as placement partners?

Reply: That’s right, even one of our own firm does that i.e. evaluation the candidates through puzzles. We do help you with that; the career cell does help you with acquiring those analytical skills as well as getting the right resources.

EPAT altogether focuses on algorithmic trading strategies, programming, statistics, financial computing (R, Python, MATLAB etc.) and strategy paradigms. We do not cover the analytical part in the EPAT given the kind of course it is but the career cell does help you on that side.

Yes, we do have a number of HFTs as our placement partners.


Question: I have a little experience in C & C++ programming working in a non-finance firm.
Right now I am looking to switch to a finance firm so that I can learn more about quant finance and HFT.
But my main aim is to be an algorithmic trader without going for higher studies.
So I am looking away from a quant developer to an analyst and then to a trader.
Can you suggest something on this?

Reply: We do have some participants in the past who took the same route. I think that can be a logical route considering you already have a strong programming experience.

As an algorithmic developer where you learn a bit about trading strategies and stats a bit to understand what you are coding and developing. But once you do that you can go-ahead as an algorithmic developer and move towards analyst and trader roles.

All in all, I think that’s a good route to go out for considering the background you just mentioned.


Question: What is the salary for a Quant and what is the demand for Quants in India?

Reply: It depends on your experience and what background you are coming from. To give you a brief idea, if the range of work experience is between 2-8 years and you are from a decent background then the quant salary typically would be somewhere in the range of 1-5 million INR on the fixed side.

It’s a broad range obviously since it depends on so many different factors hence it is difficult to give a narrow estimation.?


Conclusion

These are some of the important points that aspiring quants/developers should keep in mind as they prepare themselves for a successful career in algorithmic trading.

People often wonder:

  • how to prepare for a career in algorithmic trading?
  • how to get established in quantitative finance?
  • how to shift to the career of Algorithmic trading?
  • how to start with algorithmic trading?

Opting for professional training to learn Algo Trading is the next step in the journey. You might want to opt for a quant algorithmic trading programme which would largely benefit your skills, professional life and your career in the domain of Algorithmic Trading.

If you are a trader, a programmer, a student or someone looking to pursue and venture into algorithmic trading then our comprehensive 6 month Executive Programme in Algorithmic Trading (EPAT) taught by industry experts, trading practitioners and stalwarts like Dr. E. P. Chan, Dr. Euan Sinclair to name a few - is just the thing for you.


Disclaimer: All data and information provided in this article are for informational purposes only. QuantInsti® makes no representations as to accuracy, completeness, currentness, suitability, or validity of any information in this article and will not be liable for any errors, omissions, or delays in this information or any losses, injuries, or damages arising from its display or use. All information is provided on an as-is basis.