💡 Passionate about risk modeling, predictive analytics, financial forecasting, and big data analytics, with expertise in actuarial science, statistical modeling, and data-driven decision-making.
- Programming: R, Python, SQL, MySQL, SAS, MATLAB, HTML, CSS, JavaScript, and Excel
- Big Data & Cloud: Hadoop, Spark, AWS, Google Cloud
- Data Visualization: Power BI, ggplot2, Matplotlib, and Tableau
- Version Control: Git and GitHub
✔ Actuarial modeling – Pricing, reserving, claims analysis
✔ Time series forecasting – Volatility modeling, risk assessment
✔ Machine learning & Big Data – Predictive modeling, survival analysis, distributed computing
✔ Data visualization – Communicating insights effectively
✔ Web Applications & Dashboards – Interactive data-driven solutions
- Recognized for contributions in risk analytics, predictive modeling, and big data applications
- Successfully led 10+ data science projects in financial, actuarial, and big data domains
- Mentored 50+ students and professionals in machine learning, big data, and statistical analysis
- Yield Forecasting Model – Developed a predictive model for agricultural commodity prices
- Risk Analysis Algorithm – Built a robust framework for financial risk assessment
- Volatility Spillover Analysis – Applied TPV-VAR-SV to assess market dynamics
- Big Data Risk Analytics – Leveraged Spark and Hadoop for large-scale financial risk modeling
- Actuarial Science (Pending formal certification)
- Advanced Machine Learning & Data Science Specializations
- Big Data Analytics & Cloud Computing
- Financial Risk Management & Quantitative Analytics
- Delivered workshops on statistical programming and big data analytics for undergraduates
- Presented on predictive modeling in commodity markets at industry events
- Speaker at data analytics, financial risk, and big data conferences
🚀 Open to collaborations on actuarial science, financial risk analytics, big data analytics, and data science projects.