Associate Software Developer at Philips (2025-10 – Present)
- Developed GenAI-powered applications using LLMs and agentic workflows.
- Built and integrated MCP servers and AI agents.
- Worked on NLP pipelines, document intelligence, and retrieval systems and CNN image processing.
- Contributed to enterprise AI solutions using Python and agentic frameworks.
- Collaborated with engineering teams on work AI systems.
Independent Quantitative Researcher at Self-Directed (2023 – Present)
- Conducted extensive research on 200+ mathematical, statistical, and machine learning models for forecasting, signal generation, risk estimation, and portfolio optimization.
- Evaluated and compared model performance across multiple market regimes using real-world financial datasets.
- Researched 150+ alpha signals and quantitative factors across equities and cryptocurrency markets.
- Built systematic research pipelines for data collection, backtesting, strategy validation, and performance analysis.
- Developed volatility forecasting, market regime detection, and quantitative trading frameworks using Python.
- Collaborated with market participants by providing research insights under confidentiality constraints.
Data Analyst Intern at Futurense (2024-06 – 2024-08)
- Collaborated with a 7-member team to engineer a Flask-based full-stack application, integrating GenAI features that enhanced functionality and reduced processing time by 15%.
- Conducted in-depth data analysis for the Futurense USA Pathway Program, performing cleaning, EDA, and preprocessing to deliver actionable insights; designed an interactive Azure Data Lake dashboard.
