Imraj Singh

I am a Penultimate CS student @ National University of Singapore, and I have demonstrated a strong aptitude for solving problems having attained a top 10 ranking in NUS for a competitive programming question. My background in Computer Science has given me a deep understanding of computational thinking, which has translated to an algorithmically & mathematically inclined approach to solving problems. Having also been part of the NUS Invest club, as a Quant Finance member, I was also exposed to options pricing models as well as contributed to a semester-long portfolio optimisation project.

In addition to my STEM background, I have a strong entrepreneurial mindset of constantly finding ways to “make it happen”. During my first semester at University, I Co-Founded an Alcohol Delivery company in which we achieved superb levels of success by exploiting 2 methods I discovered. Firstly, I experimented and found a method to rank #1 on a marketplace app in Singapore, using $0 in advertising, and this went on to contribute to 70% of our sales throughout the lifetime of the company.

Additionally, I developed a social media scaling Python script, which brought our follower count organically to >1.2k followers in less than 3 months.

Quantitative Trading Intern, Infinity Capital Management, Singapore May 2023 - Aug 2023

• Work closely with the trading team to develop, backtest, & implement trading strategies using quantitative & algorithmic techniques for specific asset classes 
• Use knowledge of Deep/Machine Learning to make forecasts and develop profitable predictive trading models 
• Explore trading ideas by analyzing market data and market microstructure

• Gathered, processed & displayed IoT sensor data onto a visualization platform as part of a pitch to 4 MNCs in the Factory automation space
• Reduced expected project costs by 50% by eliminating need for physical sensors
• Wrote client-server scripts in Python, to transmit machine data via OPC UA protocol, and closely collaborated with engineers in testing of scripts, reaching a code coverage of 95% 

• Led development of a social media follower scaling script in Python, increased following to >1.2K+ followers in 3 months 
• Integrated API of fast delivery companies (GrabExpress/Lalamove) into website for ease of scaling of business, achieved an average delivery time of 47 minutes upon order
• Discovered and exploited a strategy to rank #1 in alcohol-related search rankings on Carousell, with $0 spent on Advertising, which accounted for 70% of sales
• Deployed Python Invoice Generation script on AWS Lambda, saved up to 8 hours/week of manual reporting work
• Sent automated order messages via Twilio to delivery team & streamlined communication, eliminating need to check Gmail for order information, reducing delivery times by 5 mins on average

Studying CS in NUS. Looking for a full time job.