Business Operations & AI Strategy Intern
Contributing to AI-native product strategy, market research, and go-to-market initiatives for LanternBRP — a Business Resource Planning platform focused on workflow automation and centralized data systems. Supporting competitive research and operational planning for AI tools that help SMBs improve efficiency and scale operations.
Telephone Sales
Conducted outreach to airport managers to promote and demo SaaS solutions. Scheduled follow-ups, supporting pipeline growth and product awareness.
Co-Founder
Launched and managed a home maintenance service, delivering quality results and building a loyal client base through strong customer relationships.
Analyzed 50,000 synthetic BMW vehicle sales records spanning 15 years. Explored 7 research questions including top-selling models, regional pricing, and engine-size vs. price correlation. Built 6 visualizations using ggplot2 and tidyverse. Derived a custom price_per_liter efficiency metric.
Built a fully functional vending machine in Python OOP. Implemented inventory management, a money-handling system validating $1, $2, $5 denominations, purchase flow with balance tracking, and a sales analytics method reporting per-item revenue.
Designed a Python class modeling a programmable thermostat with time-based scheduling. Stores schedules in a dictionary, sorts them chronologically, and returns the correct target temperature for any query time using clean interval lookup logic.
Deep-dive on Altai, a Microsoft Dynamics 365-based AMS. Mapped their CRM, financial management, member portal, and segmentation features. Identified gaps to inform LanternBRP product strategy around 360-degree member views and engagement scoring.
Examined the causal relationship between higher education attainment and income outcomes using public datasets in R. Applied econometric regression methods to control for confounding variables and measure the earnings premium of a college degree.
Analyzed how sensory and chemical properties of wine — texture, acidity, alcohol content — influence market pricing. Used Excel's Data Analysis ToolPak for regression modeling. R² = 0.71; alcohol and acidity were the strongest price predictors.
B.S. Administration of Economics · Secondary Major: Informatics – Data Science
Manning College of Information & Computer Sciences / Social and Behavioral Science. Relevant coursework in machine learning, public data analysis, econometrics, and financial planning. Preparing for CFP, CFA Level I, and SIE.
General Studies
Completed one semester at QCC before transferring to UMass Amherst. Finished with a 3.97 GPA.
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Feel free to reach out — I'm always open to new opportunities, collaborations, or just a conversation about data, economics, or AI.