I need someone who can help me do some data analysis of text. Specifically, in python, the freelancer will be responsible for helping me comb through a very small dataset of transcribed calls of users describing a job search process and classify the different strategies and points of failure.
The tricky part about the textual analysis is that the data is relatively small and the variety of ways that someone can describe trying to get a job is highly varied. Typical natural language process techniques may not apply, and we'll need to come up with custom classification techniques.
So for instance, someone may say (during an hour long conversation):
'I applied to 10 jobs today, but only 3 got back to me. I've been looking for work for a week and search for ads on jobs boards. A coach helped me with my resume, so i updated it and i got a few more call backs this week'.
In this small example, we'd want to classify seeing a coach and looking at a jobs board as strategies, and the number of call backs as a measure of success or failure.
The total budget for this is less than $500. There is no output, other than helping me with code and strategy. I'm a data analyst and can code in python. But, i'm not good with textual analysis.
At the end of this, we'll try to see if a machine learning classifier can recognize tags in new transcribed calls
About the recuiterMember since Mar 14, 2020 Ketan Pandey
from Ontario, Canada