Tapan Savani — Software Engineer
I am a C++ and Machine Learning developer transitioning into quantitative finance, with expertise in low-latency systems, statistical modeling, and time series forecasting. Proficient in C++ and Python. Currently working at Samsung R&D on real-time deep learning based model fintuning and cpp based inference pipelines, I bring expertise in C++ (multithreading, lock-free data structures, memory models) and Python (time series data analysis, statistical modeling). Designed and built TapQuant, a research-driven trading platform that combines low-latency C++ infrastructure with scalable Python analytics, supporting both rapid strategy research, Implementation and analysis. 🔹 Core strengths: - C++ (low-latency, concurrency, memory optimization) - Quantitative finance (portfolio theory, Black-Litterman, VaR, risk modeling) - Machine Learning & Deep Learning (CNN, LSTM, feature engineering) - Time Series Forecasting (SARIMA, GARCH, volatility modeling) I am passionate about solving complex problems at the intersection of finance, mathematics, and high-performance computing, and I aim to contribute to quant trading and research roles where performance and precision drive alpha.
Stackforce AI infers this person is a Backend-focused Software Engineer with expertise in SaaS and quantitative finance.
Location: Noida, Uttar Pradesh, India
Experience: 2 yrs 11 mos
Skills
- C++
- Machine Learning
- Backend Development
- Cloud Integration
Career Highlights
- Expert in C++ and Machine Learning for finance.
- Designed a low-latency trading platform.
- Proven track record in real-time systems development.
Work Experience
Samsung Electronics
Software Engineer (2 yrs 2 mos)
TECHstile
Software Developer (6 mos)
Software Developer (2 mos)
techmihirnaik Group
Back-end Developer (3 mos)
Education
Bachelor of Technology - BTech at Indian Institute of Information Technology Vadodara