Hello, I'm
Atul Vinod
About Me
I'm an MBA student with a Computer Science background, passionate about bridging the gap between technical analytics and business strategy.
My journey started with building software, but I quickly realized the real impact comes from turning data into decisions. Whether it's optimizing investment portfolios, detecting fraud patterns, or uncovering customer insights—I love solving problems that matter.
Currently, I'm focused on machine learning applications in finance and exploring how AI can make enterprise risk management more accessible to decision-makers.
When I'm not diving into datasets, you'll find me exploring new tech, reading about behavioral economics, or experimenting with side projects that probably won't make money but will definitely teach me something.
Credentials
AWS Cloud Practitioner
Featured Projects
Enterprise Risk Management
The Problem
Financial institutions struggle to separate genuine fraud signals from operational noise, leading to alert fatigue and missed threats.
My Approach
Built a hybrid anomaly detection system combining statistical methods with ML classifiers, then translated technical scores into business-readable "Risk Drivers" using SHAP explainability.
The Results
- 40% reduction in financial risk exposure
- Accelerated security audits with executive-ready dashboards
- Actionable insights replacing black-box predictions
Quantitative Portfolio Optimization
Monte Carlo simulation engine for maximizing Sharpe Ratio and analyzing VaR. Features real-time data fetching and interactive Efficient Frontier visualization.
E-Commerce Strategic Analysis
RFM segmentation and cohort analysis to identify "Champions" and "At Risk" customers. Transforms raw transactions into actionable retention strategies.
Skills & Tools
Data & Analytics
Python
Pandas
NumPy
SQL
Visualization & ML
Matplotlib
Seaborn
Cloud & Infrastructure
AWS
"The best analysts don't just crunch numbers—they translate complexity into clarity. That's where real business value is created."