As a Distribution Analyst for the Daily Californian newspaper, I used Python, Excel spreadsheet analytics and strategic A/B testing, to direct the improvement of the readership rates for the paper.
My cover letter used to say “As a distribution analyst at the Daily Californian, I challenged the status quo of our business operations using Excel spreadsheet analytics and strategic A/B testing to push our readership percentage to new peaks. Through weekly reports and creative project proposals, I have helped to lowered return rates of the daily papers by 50% in a year.”
Effectively, my job was to direct the process improvement for the weekly circulation of 40,000 newspapers over 150 drop locations in Berkeley. I worked with with a team of six in operational advisory, decreasing rate of return by 25% over a 6-month period through various data metrics such as strategic A/B Excel testing. Our job was effectively to analyze readership data, which we did through the filing of six weekly reports and three monthly reports to develop and propose changes to distribution strategy for the newspaper.
We also undertook, designed and prepared creative ways to improve the return rates of Daily Californian boxes. One of mine included decorating a box as a ghost for halloween. (It was pretty cute in my opinion.)
My least favorite part of the job was to enter daily return rate and location information from distributor reports into Excel spreadsheets to ensure proper data analysis and collection. I tried to avoid this data entry work at all costs.
This was a really fun job and actually a great way to get experience in data science. It was effectively a college newspaper but working 10 hours per week there was really useful in landing my first real jobs.
WORK SAMPLE: https://drive.google.com/open?id=1_apnvFBHXi3GgBQYpn0m6WAslpZwvJpv