Business Analysis & Data Strategy

My Unique Perspective to Analytics

I bring a unique perspective to business analysis shaped by a multidisciplinary education. I hold a Master of Science in Business Analytics from Carnegie Mellon University’s Tepper School of Business, where I specialized in advanced data modeling and machine learning applications for business strategy. I also earned a Master of Science in Journalism (Data Specialty) from Columbia University, which trained me to extract clear insights from complex datasets and communicate them with impact.

My foundation began with a Bachelor of Arts in Neuroscience from Wheaton College (Massachusetts), where I developed a strong grounding in research and analytical methods. To further sharpen my technical expertise, I am completing an Executive Certificate in Artificial Intelligence from Columbia Engineering, deepening my skills in AI-driven business solutions.

  • CMU Capstone 2025: Integrated Analytics Project

    CMU Capstone 2025: Integrated Analytics Project

    Led a semester-long project at Carnegie Mellon combining data engineering, predictive modeling, and business strategy. Created dashboards, ran statistical and ML analyses. Delivered insights supporting investment decisions, risk assessment, and portfolio optimization.

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  • Graph with candlestick and line charts overlaid, text overlay reads 'Stock Analysis & Prediction Models'.

    Stock Analysis & Prediction Models

    Built a suite of notebooks exploring stock market trends, price forecasting, and technical indicators. Applied time-series models, feature engineering, and backtesting to evaluate predictive performance. Clear visualizations helped communicate model behavior to decision makers.

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  • Title slide for a presentation titled 'Diabetes Prediction Analysis' with a subtitle '(Pima Indian Female Patients)'. The background has medical icons, including a stethoscope, a droplet, a heartbeat line, a pie chart, and a human torso outline with lungs, on a blue grid background.

    Diabetes Prediction Analysis (Pima Indian Female Patients)

    Performed classification modeling to predict diabetes outcomes in the Pima Indian dataset. Used logistic regression, decision trees, and ensemble methods. Emphasized data cleaning, feature selection, and validation. Results improved classification accuracy and highlighted key risk factors.

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  • Blue graphic with white text reading "Advanced Analysis of Real Estate Valuation & Seed Germination Data" alongside illustrations of a growth chart, a house, and a sprouting plant.

    Advanced Analysis of Real Estate Valuation & Seed Germination Data

    Analyzed real estate valuation and seed germination datasets using statistical modeling and exploratory data analysis. Compared key predictors for property prices while investigating biological growth under varying environmental conditions. Delivered insights using visualizations and regression techniques.

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  • Title slide with blue background, a medical caduceus symbol on the left and a computer monitor icon on the right, displaying the text 'Analysis of CDC's health data & UX improvement experiments' in white.

    Analysis of CDC’s Health Data & UX Improvement Experiments

    Worked with large public health datasets from the CDC. Cleaned and visualized trends in morbidity/mortality and demographic factors. Ran user-experience experiments to test data presentation formats. Proposed UI/UX improvements for dashboards to make health data more accessible.

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  • Blue background with a technological design, featuring the text "AI BLOG TEXT GENERATOR" and icons representing an AI chip and chat bubbles.

    AI Blog Text Generator

    Built a PHP-based text generation tool designed to help create blog content with AI. Focused on automating portions of writing workflow, allowing customization of topics, tone, length, and incorporating user feedback. Showed how machine-generated text can support content creation while maintaining editorial voice.

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