Francesca Kubica

About Me
Hello! I am Francesca, a first-generation student from Gilroy, California. If my friends were to describe me in three words, it would be: optimistic, ambitious, and curious. A few things that I love are cats, fashion, pink, and the history of humankind. I’m captivated by the intersection of finance and technology, and could talk your ear off about personal finance. In my free time, I enjoy active sports (hiking, pickleball, weight lifting), reading, and baking. My current fascination, as of writing, is having old-fashioned tea parties with crumpets.

What are some of your key professional/career interests?
I am passionate about finance, data, and strategy. As a long-term career goal, I want to be in a finance strategic role at a large tech company in the Bay Area. To get there, I’m looking for experience in Business Intelligence and Data Science.

What are some of your skills?
Data Visualization, Machine Learning, Optimization Programming, Dashboarding, Leadership, Communication, Attention to Detail

What are some relevant classes/coursework you have taken?

Artificial Intelligence Principles and Foundations (CSCI 360), Statistics and Data Science for Business (BUAD312), Corporate Finance (BUAD306), Advanced Operations Management and Analytics (BUAD313), Data Structures and Algorithms (CSCI 104), Financial Accounting/Managerial Accounting (BUAD280/281)

What are some of your projects or achievements?

I worked as a Finance Business Intelligence Analyst at Google in the Financial Planning and Analysis Hub team this summer, June 2025 - August 2025. My summer project was split into two parts: data analysis/dashboarding for senior leadership, and model experimentation for a Bayesian Hierarchical Model that forecasts all of Google's non-payroll OpEx Month-End Close expenditure. I leveraged SQL to find a respective month for cost centers across Google Finance to begin capital reallocation decisions, with an opportunity to reallocate 3% of OpEx budget. I presented these findings to the Senior Director of Finance and developed a prototype of an automated dashboard that can improve budget utilization as early as June by 15% for each cost center. For my second project, in python I completed exploratory data analysis to understand expenditure trends, seasonality, and statistical properties for a subset of the total data, focusing on the Finance cost center. Then, I feature-engineered lags, rolling averages, and data-based features to train an XGBoost model and conducted a model performance comparison of my model and the baseline BH model. To complete this project, I was mentored by a Staff Data Scientist in the Data and Analytics team at Google Finance.