Aspiring Data Analyst | Payments & Fraud Analyst | SQL • Python • Power BI
I love working with data, uncovering patterns, and building dashboards that tell meaningful stories. With a background in transaction monitoring and fraud prevention, I combine analytical skills with domain expertise to detect anomalies, reduce risks, and support decision-making.
- Data Analysis: Exploring datasets, performing EDA, spotting trends, and solving real-world business problems.
- Statistics: Descriptive statistics, hypothesis testing, probability concepts, and time series analysis for data-driven insights.
- Fraud Analysis: Transaction monitoring, anomaly detection, risk evaluation, and understanding fraud patterns like chargebacks, ATO, ACH issues, and money-mule activities.
- Languages: SQL, Python
- Python Libraries: Pandas, NumPy, Matplotlib, Seaborn
- Tools: MS Excel, Power BI
- Visualization: Matplotlib, Seaborn, Power BI Dashboards
- Transaction Monitoring
- Chargeback Analysis
- Account Takeover (ATO)
- ACH Return Analysis
- Fraud Pattern Recognition
- AML Red Flags & Risk Indicators
- Descriptive Statistics
- Hypothesis Testing
- Time Series Analysis
- Exploratory Data Analysis (EDA)
- Data Cleaning & Feature Understanding