Sidhant Bansal

Quantitative trader at Tower Research Capital in New York City since June 2025, on the Limestone Pod Core Machine Learning team. Previously a quantitative trading intern at Tower (2024), a full-time software engineer at Citadel Securities in London and New York (2021-2023), and developer interns at DRW (2020) and Jane Street Capital (2019). Holds an MS in Computer Science from Stanford University (2023-2025) and a BComp from the National University of Singapore (2017-2021). Represented India at the International Olympiad in Informatics in 2017, winning a bronze medal, and maintains a public competitive-programming profile.

Notes5

• Quant employment verification: CONFIRMED. The self-authored resume (sidhantbansal.com/resume.pdf) and about page establish a supported identity (Sidhant Bansal, IOI 2017 India, Stanford MS CS, NUS BComp) and list actual roles/internships at genuine quantitative-finance employers: Tower Research Capital (Quantitative Trader, full-time 2025-present; Quantitative Trading Intern 2024), Citadel Securities (Software Engineer, full-time 2021-2023), DRW (Developer Intern 2020) and Jane Street Capital (Developer Intern 2019). Employer classification: Tower Research Capital is a proprietary/high-frequency trading firm; Citadel Securities is a market maker; DRW is a proprietary trading firm; Jane Street Capital is a proprietary trading/market-making firm - all operate in quantitative/systematic trading, not merely names containing 'quant'. These are actual roles/internships, not student programs. LinkedIn index enrichment corroborates the same employers but is index-only and not treated as independent confirmation.Sep 17, 2026
• Full-time Quantitative Trader at Tower Research Capital since June 2025 (Limestone Pod, Core Machine Learning team) in New York City; resume states research into linear and non-linear modeling techniques to strengthen alpha across datasets and time-horizons.Jun 2025
• Quant Trading Intern at Tower Research Capital, June-August 2024, New York City, improving target correlation 11% (relative) in futures markets via an attention-based neural network.Jun 2024
• MS in Computer Science (Theory track) at Stanford University, 2023-2025, GPA 4+/4.0, overlapping the 2024 Tower intern stint; TA for Mining Massive Datasets and Modern Algorithmic Toolbox.2023
• Software Engineer (full-time) at Citadel Securities, August 2021-June 2023, London and New York City; built a C++ real-time reconciliation service for 100M+ daily orders and worked on the options team's corporate-actions pipeline.Aug 2021
• Won a Bronze medal representing India at IOI 2017 (International Olympiad in Informatics); IOI statistics list him as India contestant with a 90.00 score.2017
• Research at Stanford Impact Lab on Algorithmic Market Design (March 2024-March 2025) with Prof. Itai Ashlagi and Prof. Irene Lo: improved multinomial-logit models to forecast student preferences for San Francisco public-school allocation and simulated policy designs presented to SFUSD.Mar 2024
• Developer Intern at DRW, May-August 2020, Singapore: exchange market-data compression tooling and the 'conda compare' feature in Conda.May 2020
• Developer Intern at Jane Street Capital, May-August 2019, Hong Kong, across post-trade and trading-system teams in OCaml.May 2019
• BComp in Computer Science at National University of Singapore, 2017-2021, GPA 4.8/5.0, Turing Programme with a Minor in Mathematics; coursework included randomized algorithms, convex optimization and game theory.2017
• Undergraduate final-year thesis at NUS on 1-bit compressed sensing (April 2020-Jan 2022) under Prof. Arnab Bhattacharya.Apr 2020
• Earlier software engineering experience at Xfers (YC Summer 2015 startup, Singapore) as a full-stack engineer in 2018, and as an ICPC Indian Regionals problem setter 2017-2018.2018