CQF alumnus, Alok Jadhav, is a Quantitative Developer at y-intercept in Hong Kong. Alok studied Computer Science at the Pune Institute of Computer Technology before gaining a M.Tech in Computer Science from the Indian Institute of Technology. He started his career as an Automated Trading Strategy Developer for Credit Suisse. It was during this time that he decided to enroll on the CQF to gain essential quant skills needed to progress his career. We caught up with Alok to find out more about a typical working day in his current role.
I work at y-intercept as a Quantitative Developer, where I am responsible for the execution platform for the trading desk. This platform receives target portfolios from a quantitative trading team that need to be executed over the day. Some orders are meant to be forwarded to broker algos, while others are to be executed internally in a smart way, with the aim of reducing trading costs. Lately, most of my time is spent on a new application called the Algo Engine which is in the very early stages of development. Below, is my typical working day as a quantitative developer:
08:30 AM:
I usually arrive at the office, get to my desk, check my emails, and respond to anything urgent. Next, I prepare for my daily meeting at 9 AM.
09:00 AM:
I attend a daily stand up meeting with my team. During this meeting we review and update the status of work done the previous day and plan the day’s tasks (which will be followed up on the next day). This meeting usually lasts for 10 to 15 mins. After the meeting, I review my items for the day and get started. By 09:30 AM, I am completely focused on the tasks I have at hand. Usually, I have one main task for the day or a few minor tasks. I typically use morning hours to do the development work and post-lunch hours are used for meetings and research.
10:00 AM:
I keep working through my daily tasks. For example, today I noticed that one of the equity index futures didn't roll automatically in EMEA last night. After investigation I discovered that we had an exceptionally large quantity to trade yesterday and the trading couldn't complete automatically due to constraints. I notified the team about the cause of incompletion and asked the users to roll the remaining quantity manually. One of the EMEA commodity futures had an adverse execution price for yesterday, so I then spent some time investigating the execution behavior and sharing the details with the traders. With no more pending issues, I then focused my efforts on the algo engine development.
For the next one to two hours I focus purely on the completion of my development tasks. While doing this, I also check that the systems are working correctly in production. We use Slack for all business communication – so the Slack channel for production is always open on one of my screens and I regularly check the discussion going on in this channel. If there are any issues with one of my applications, one of the support team members will try to resolve this. However, if they are not able to resolve it, I or another dev team member will look into the issue urgently.
11:30 PM:
It's time for lunch. This is usually a good time to catch up with colleagues. Sometimes I go out with colleagues, and other times I eat at my desk, reading the news or surfing the web. I usually finish my lunch in half an hour and have a short break of 15 minutes.
12:15 PM
I continue to work on the Algo Engine development. It's a big project and still in the early stages. We use a JIRA board for tracking our deliverables. For development, we follow the TDD approach where you write the test cases before you write the actual code. Currently, I am setting up the algo engine in backtesting mode which will aid in doing further development and enable us to check the execution performance.
02:30 PM
If there were no production issues and no other meetings for the day, I usually go to the gym around this time (it helps that the gym is in the same building as our office). Usually, I return to work around 3:30 to 3:45 PM.
04:00 PM
I research new financial papers that could be useful for the Algo Engine – I typically look for papers on optimal execution models, order placement strategies etc. I then continue to work on development -closing those Jira tasks one by one. If there were any issues reported with any of them, I resolve those issues and plan for a release. Some issues are urgent and require an urgent patch and release without waiting, whereas other issues can be aligned in the next release of the application.
05:00 PM
I catch up with other team members on issues pertaining to my projects and set up follow up meetings with other teams. I also use this time to catch up with the data team on any data requests. I then have a status meeting with the management team where we discuss the longer-term plans for the execution platform.
06:30 PM
I am done for the day and head home. I usually check my Slack messages at home but I don't log back into work unless required in the case of urgent production issues.
Find out more about Quantitative Developer Careers
If you are interested in becoming a quantitative developer, explore the new CQF Careers Guide to Quantitative Finance. Learn more about the skills needed and average salary you can earn in North America, Asia, and Europe for key career paths in quantitative finance.
