Rahul Kumar Singh

About Rahul Kumar Singh

Quantitative Developer specializing in algorithmic trading systems, low-latency data pipelines, and scalable research infrastructure.At PinSec.Ai, I build end-to-end trading infrastructure—integrating multi-source market data (Kite, XTS, TrueData, GDF), architecting InfluxDB time-series storage, and automating research-to-live workflows. My work bridges quant research and production execution with a focus on reproducibility, system reliability, and latency optimization.Previously at BlackBox Securities and iRage, I contributed to backtesting frameworks, live execution models, and analytics for market-making strategies in equities and crypto. I began at Amazon, improving NLP data quality for Alexa.Currently pursuing MSc in Financial Engineering from WorldQuant University. Passionate about alpha research, data-driven trading automation, and scalable quant infrastructure.Core Areas: Algorithmic Trading | Quantitative Research | Market Data Engineering | Python | InfluxDB | REST APIs | Backtesting Frameworks | Trading Automation

Experience

1. Quantitative Developer

   Pinsec.Ai

   Aug 2024 — Present · NY, US

   1 : Data Engineering & ETL1.1 Built multi-source market data pipelines integrating Kite, XTS, TrueData, Irage, and GDF APIs.1.2 Designed InfluxDB schemas for efficient tick-level and time-series data storage.1.3 Automated historical and live data ingestion with synchronization and error recovery logic.1.4 Developed monitoring and recovery scripts ensuring stable and continuous data flow.2 : Quant Research2.1 Designed and backtested quantitative strategies including Mean Reversion (EMA, RSI, BB) and SuperTrend models.2.2 Developed a portfolio-level backtesting framework supporting Sharpe, Sortino, and drawdown analytics.2.3 Performed root-cause analysis on data inconsistencies to enhance model stability and research accuracy.3 : DevOps & Infrastructure3.1 Supported server migrations and environment standardization across research and production.3.2 Implemented REST API automation for execution, data capture, and analytics workflows.3.3 Created Telegram bot utilities for internal alerts and system monitoring.3.4 Optimized system throughput and latency using Python multiprocessing and asynchronous processing.4 : Quant Developer4.1 Developed modular Python systems connecting live execution with backtesting environments.4.2 Built data validation tools ensuring alignment between research outputs and live data.4.3 Automated strategy deployment and log analysis pipelines for continuous monitoring and reporting.Skills: Algorithmic Trading · Quantitative Research · Data Engineering · Python (Programming Language) · InfluxDB · REST API Development · Linux · DevOps · Automation · Market Data Infrastructure

Education

• Kendriya Vidyalaya

  HS, Commerce with Maths

• Tezpur University

  B.Com (Hons), Banking and Finance

• Kendriya Vidyalaya

  10, General

• WorldQuant University

  MSc Financial Engineering