Data Projects
Predictive Analytics Project: First Destination Career Survey
Ev
ery year, Biola’s Career Center sends out a survey to the previous year’s grads, asking what jobs alumni landed in directly out of college.
I wanted to know: what a student can do during college that will increase their odds of landing in a job they like in the first year out of school? Is it internships? Paid internships? A specific major?
So I initiated, designed and delivered an analytics project based on that data to identify activities that increase a graduate’s ability to find a full-time job that they are satisfied with in the year after graduation. I then
recommended changes in Career Center engagement strategy based on results.
What I did
Data cleanup: Cleaned 7,000+ rows of survey data from the past 5 graduating classes in Excel, joining it with Career Center 32,000+ records of student appointments in Power BI
Exploratory Data Analysis: Designed visualization dashboard in Power BI to look at alumni outcomes by major, industry, job satisfaction and more.
Descriptive Data Analysis: Created 3 hierarchical clustering models using Python in Jupyter Notebooks and analyzed clusters for patterns, using Excel to describe and visualize demographics within clusters
Predictive Data Analysis: Produced 2 classification trees to predict graduates’ employment and job satisfaction based on undergraduate internship participation, Career Center appointments and major choice
Actionable Recommendations: Summarized and presented results, including data visualizations, explanation of the predictive model and recommendations for changes in student engagement strategy.
What I found:
I made a presentation that explains everything you need to know about the data, how I analyzed it and what I concluded.