In my current role as a Data Scientist consulting with federal government clients on data projects, I leverage powerful tools to extract actionable insights from large and complex datasets. I use programming languages such as Python and R and visualization software such as Tableau to cleanse, analyze, and visualize data. I am passionate about using data science techniques and methodologies to enhance data processes and implement data-driven solutions for my clients.
I work with multiple federal government clients to consult on data projects. I develop data tools and dashboards for the President’s Malaria Initiative (PMI) through USAID, which includes processing, cleaning, and performing quality control checks on epidemiological data from 27 countries, building data product MVPs, and soliciting client feedback to develop and improve multilingual Tableau and R Shiny reports. I also lead multiples workstreams for the Office of Personnel Management (OPM) client engagement highlighting and analyzing patterns in the federal hiring process. I scoped, demoed, and developed a Flask app that provided a non-technical client with an interactive and descriptive view of federal hiring success rate across department, agency, location, and other variables. I also analyzed the attrition rate of new federal hires during onboarding by developing methodology to extract statistical outliers and highlight applicants who dropped out.
As analyst, Consumer and Shopper Marketing R&D, I was responsible for deliverables pertaining to IRI’s proprietary ShopperSights tool. I used Alteryx to automate QCs of the ShopperSights store file and build IRI Proscores for Trade Areas that rank the purchase propensity of over 23 million consumer households using POS data. I also utilized Python, APIs, and Javascript to cleanse and manipulate POS data, panel data, and survey data for ad hoc projects related to custom Mosaic mappings, power of household modeling versus block group modeling projections, and other data-driven analyses.
I analyzed big data patterns in restaurant chains, including food sales, alcohol sales, dining segment trends, and demographic trends. I cleansed and analyzed data by building pivot tables and performing V- and H- lookups in Excel, and I created data visualizations for client data presentations. I also performed ETL procedures to load data into the proprietary data warehouse after first extracting restaurant attributes using the Yelp API and cleansing with Pandas in Python.
A 24-week intensive certificate program focused on gaining technical programming skills in Excel, VBA, Python, JavaScript, SQL and NoSQL Databases, Tableau, D3, HTML, Web Scraping, AI, and Machine Learning
Coursework included: Real Analysis, Complex Analysis, Multivariable Calculus, Linear Algebra
Coursework included: Econometrics, Probability and Statistics, Microeconomics, Game Theory, Introduction to Non-Profit Consulting
Completed Senior Thesis focused on analyzing city government crime data in Philadelphia, PA using geomapping techniques
Completed study abroad semester at Sorbonne Université in Paris, France
SAT: Math: 770 / 800 · Critical Reading: 800 / 800 · Writing: 800 / 800 | ACT: 35 / 36
Using data from various sources, I graphed the relationship between a country's Gender Gap Index and the percent of females graduating from STEM fields in tertiary education. I also analyzed how GDP relates to these measures.
I used the SeatGeek API to collect the median ticket price of all Phillies games in a SQL database (utilizing SQLAlchemy). I then analyzed these findings and presented them in a Tableau visualization.
Apart from exploring and analyzing data, I enjoy being active and running and have participated in several races, including the Big Ten 10K in Chicago, IL and the Army Ten-Miler in Washington, D.C.
I also volunteer with Capital Partners for Education as a mentor to a high school student on their journey to attend college.
I'm also a proud fan of the Washington Nationals! Go Nats!