- 👩💻 Professional Expertise: With 10+ years in IT and Data Analytics, I specialize in translating complex data into meaningful financial insights. Currently working at Capco Technologies, I blend technical proficiency with financial intuition to automate workflows and analyze investment opportunities at scale.
- 🎓 Academic Credentials: M.Tech in Data Science & Engineering (BITS Pilani, 2024). Deepening my expertise in finance, risk, and portfolio theory—bridging the gap between tech and financial markets.
- 📍 Location: Based in Delhi, India.
I am driven by the intersection of data science, AI, and financial strategy. Whether it's backtesting a trading idea, building predictive models, or exploring market microstructures—I enjoy uncovering hidden signals in data that can drive smart investing decisions. My work integrates automation, technical analysis, and financial modeling to support robust and scalable wealth strategies.
- Programming & Data: Python, PySpark, SQL
- Tools & Platforms: JIRA, GitHub, PostgreSQL, VSCode
- Visualization & Reporting: Power BI, Apache Superset (open-source dashboarding)
- Quant & Technical Analysis:
- Indicators: RSI, MACD, Bollinger Bands, Ichimoku Cloud, Fibonacci, Kurtosis
- Time Series Modeling & Forecasting
- Pattern Recognition & Signal Detection
- Portfolio Theory:
- Sharpe Ratio, Risk-Adjusted Returns
- Asset Allocation & Diversification Strategies
- Machine Learning:
- Predictive Modeling of Market Behavior
- Exploratory Factor Analysis and Sentiment Signals
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⚙️ Automated Financial Data Pipeline
Designed and deployed a Spark-based pipeline to ingest, process, and analyze market indices at scale—reducing manual intervention and increasing accuracy. -
📈 Visual Insights into Markets
Built interactive time-series dashboards for key indicators (RSI, MACD, etc.) that support real-time investment decision-making. -
🧠 AI-Enhanced Market Intelligence
Researched and prototyped AI-based models to augment traditional financial analysis and extract high-alpha signals from alternative data. -
📊 Simulated Portfolio Engine
Built a Python-based simulator to test various portfolio construction strategies using historical data, optimizing for return vs. volatility.
I envision myself evolving into a Quantitative Researcher focused on applying data science to solve high-impact problems in investing, risk, and wealth creation. I believe in rigorous analysis, disciplined execution, and continuous learning to navigate complex financial systems.
Whether it’s ESG investing, macro trend modeling, or statistical arbitrage—I am excited to contribute to teams working at the frontier of finance and technology.
Explore my repositories and feel free to reach out. I’m always up for conversations around financial modeling, quant research, or building intelligent investment tools with open-source tech.