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kumarritik24/README.md

Hi, I'm Ritik Kumar πŸ‘‹

πŸŽ“ MS in Information Technology & Analytics from Rutgers Business School - Newark
🌍 International student | Open to full-time roles in the U.S. (sponsorship needed starting 2028)
πŸ’Ό Actively seeking roles in Anti-Money Laundering (AML), Risk Analytics, Data Analysis, Business Intelligence, and Tech
πŸ”— Connect with me on LinkedIn


πŸš€ About Me

  • 🧠 Passionate about data-driven storytelling and real-world impact
  • πŸ” Skilled in Anti-Money Laundering (AML), Financial Data Analysis, Data Engineering, Business Intelligence, Compliance, and Analytics
  • πŸ’‘ Experience working on fraud detection (Airbnb), cost optimization (healthcare), and churn prediction projects
  • 🌱 Currently learning: Alteryx, Power BI Advanced, and ML for Risk Modeling
  • βœ‰οΈ Fun fact: I enjoy simplifying complex data into actionable dashboards and visuals!

πŸ› οΈ Tools & Technologies

AML/KYC Tools OFAC/BSA Refinitiv WorldCheck Alteryx logo

Languages:        Python, R, SQL, HTML/CSS, SAS
Libraries:        Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn
BI Tools:         Power BI, Tableau, Excel, WorldCheck, Jupyter
Automation:       Alteryx (Fundamentals Completed), Airflow, Apache Spark, Apache Beam
Cloud & Data:     Snowflake, GCP, AWS, Azure, Docker, Kubernetes, Terraform, MySQL, PostgreSQL, MongoDB, AlloyDB, Oracle, Amazon S3, Redshift
Version Control:  Git, Bash, GitHub

πŸ“Š Projects Summary

Project Title Tools Used Highlights
Uber Trip Analysis Python, Pandas, Jupyter Visualized NYC Uber trip patterns and peak-hour demand trends
Air Pollution Analysis Tableau, Excel Visualized global pollutant trends and regional disparities over time
Healthcare Cost Optimization Excel Forecasting Achieved 18% cost savings using break-even & dosage trend analysis
Titanic ML Python, Scikit-learn, ML Models Predicted passenger survival using classification techniques
StackOverflow Forecast Python, ARIMA, Holt-Winters Forecasted Python-related questions on Stack Overflow
NJ Home Price Forecasting R, Holt-Winters, ggplot2, forecast Predicted housing price trends in New Jersey using time series models
DC Industries Sales Optimization Alteryx, Excel, ETL Automated ETL to merge regional sales data, identified underperforming categories, and reduced manual reporting by 40%

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  1. Uber-Trip-Analysis-in-NYC Uber-Trip-Analysis-in-NYC Public

    Visual exploration of Uber ride patterns in NYC using Python. Identifies peak demand times, geospatial hotspots, and weekday vs. weekend behavior trends.

    Jupyter Notebook 1

  2. Sales-Performance-Optimization-DC-Industries Sales-Performance-Optimization-DC-Industries Public

    Automated ETL workflow in Alteryx to analyze regional sales data and generate KPIs for business strategy.

  3. Air-Pollution-Analysis-Dashboard Air-Pollution-Analysis-Dashboard Public

    Interactive Tableau dashboard analyzing global air pollution trends by country, pollutant type, and year. Visualizes disparities, emissions patterns, and improvements over time.

    1

  4. Stack-Overflow-Python-Trends-Forecasting Stack-Overflow-Python-Trends-Forecasting Public

    Time series forecasting of Python-related questions on Stack Overflow using ARIMA and Holt-Winters models. Insights support trend analysis and future tech curriculum planning.

    HTML

  5. Titanic-Survival-Prediction-using-Machine-Learning Titanic-Survival-Prediction-using-Machine-Learning Public

    This project applies Machine Learning techniques to predict the survival of Titanic passengers. It explores various data preprocessing, visualization, and model-building techniques to enhance predi…

    Jupyter Notebook

  6. NJ_Home_Price_Forecasting NJ_Home_Price_Forecasting Public

    Forecasting New Jersey home prices using R time series models. Includes Holt-Winters, SES, and trend decomposition to predict housing market trends.

    HTML

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