Member of Questa software product team, providing hardware verification and digital design simulation capabilities.

• Achieved a 40% reduction in Questa HDL parallel simulation execution times through the implementation of smart profiling-driven rebalancing of execution patterns, demonstrating proficiency in C, MPI, and GDB.

• Automated the merging of log files from parallel simulations, creating a unified view for streamlined analysis and debugging.

As an R&D team member, I specialized in building components for advanced trading systems, acting as an analytic engine, portfolio optimizer, and risk manager.

Some of my best projects during this time include:

• Accelerated historical financial simulations and risk reporting by 80% in C++ by optimizing state file memory load time. Utilized multithreaded decompression with the lz4 library and parallel deserialization using Boost thread pool.

• Strengthened security of 3 major trading systems by integrating TLS protocol into all C++/Python socket communications. Leveraged the OpenSSL library to enable robust authentication and encryption mechanisms.

• Implemented a price update module for ETFs, leveraging Apache Kafka to receive real-time quotes and efficiently handle up to 10K messages/second. Ensured precise and timely pricing for effective trading decisions.

• Developed 50+ optimized quant metrics in C++/Python for security modeling, portfolio management, and risk analysis.

• Actively took the lead in interviewing candidates for internships and full-time Software Engineering roles, contributing to the growth of our team.

• Initiated and participated in an outreach initiative called Ascend Educare, where I taught Object-Oriented Programming (OOPs) and C++ concepts to undergraduate students, helping them enhance their skills and knowledge in the field.

As a junior R&D team member, I immersed myself in the world of advanced trading systems, serving as an analytic engine, portfolio optimizer, and risk manager.

My primary focus was on financial time-series data, and some of my proud projects include:

• Accelerated access to financial time-series data (over 25 TB) by an impressive 2000% compared to Data Warehouse queries. This achievement was made possible by developing a high-performance vectorized cache library in Python, leveraging NumPy and HDF5 file format.

• Facilitated historical data access for 12+ strategy teams by creating GraphQL APIs over Django. These APIs were seamlessly integrated with the cache library, ensuring cross-language compatibility, flexible queries, and efficient data retrieval.

• Reduced cache maintenance and update requests by a substantial 80% by devising a highly flexible mechanism in Python. This allowed for seamless modification to the underlying cache configuration.

• Developed interactive visualizations for historical stock and portfolio data analysis, leveraging React, D3.js, and Django backend.

• Improved developer productivity by significantly reducing the build time of the 100K+ lines of C++ codebase by 60%. This achievement was accomplished through the implementation of CMake, ccache, migration to C++14 from C++98, and upgrading the GCC version.

Devised a specialized genetic algorithm to optimize target tracking by surveillance agents with restricted visibility, implementing a CUDA-based parallel version in C++ for strategy testing, resulting in over 70% successful agent tracking across 5000-time steps.