I’m self taught but I have a background in data as it relates to commercializing pharmaceuticals. Since I decided to switch to data (early 2022) I have squeezed as much data experience out of my job as I could, mostly by replacing all visualization tasks the group used excel for with BI. I sold it to my boss as “data automation.”
As for improving employer response rate: local (non remote) jobs, certs, and analyst vs scientist/MLE. I improved as i went. 450 apps is over the course of 12 months is only 1.2 per day. As I interviewed and saw what got/didn’t get traction my approach changed. Also note that while I sent out ~450 apps, ~350 of those were for dat scientist positions which I shouldn’t have been applying for in the first place.
I had 2 interviews for data analyst position off of 100 applications in an economy that had just laid off 5-10% of tech. During this time I was constantly tweaking my resume. Both interviews were off of the last batch of ~20 apps I sent out in late march, early April. one ghosted prior the the initial interview the other interview I nailed with the help of Raptor.
Hey OP,thanks for sharing your path to become a data analyst.So you recommend to ignore python for now and learn Sql and tableau/Power BI first right?And you think there are still entry level positions out there?I read companies are looking for more advanced Data analysts.I would love to hear your thoughts
Raptor recommends familiarity with python or R for data analysts and proficiency for scientists/MLE. Also recommends to start as an analyst to build up experience/proficiency.
I thought I could skip that step and went hard into python to start, it would have been more efficient to just execute the in blog python/r coding (probably a month or so of work) then go hard at SQL, get the cert, start applying while simultaneously going hard at BI and getting the cert.
There’s definitely entry level positions. They might be contract/temp agency work (raptor would have better insight than me since I am just entering the industry) but they are there.
And raptor if I’m misrepresenting your views in any way, please correct me.
Got a few questions for OP:
Do you have any formal CS or DS education or are you just self taught + a few certifications.
450+ applications for 10-ish interviews is very machine gun-y, do you have any specific tips on how to improve your win rate.
Good luck with your new job, an update post a few months later would be nice
I’m self taught but I have a background in data as it relates to commercializing pharmaceuticals. Since I decided to switch to data (early 2022) I have squeezed as much data experience out of my job as I could, mostly by replacing all visualization tasks the group used excel for with BI. I sold it to my boss as “data automation.”
As for improving employer response rate: local (non remote) jobs, certs, and analyst vs scientist/MLE. I improved as i went. 450 apps is over the course of 12 months is only 1.2 per day. As I interviewed and saw what got/didn’t get traction my approach changed. Also note that while I sent out ~450 apps, ~350 of those were for dat scientist positions which I shouldn’t have been applying for in the first place.
I had 2 interviews for data analyst position off of 100 applications in an economy that had just laid off 5-10% of tech. During this time I was constantly tweaking my resume. Both interviews were off of the last batch of ~20 apps I sent out in late march, early April. one ghosted prior the the initial interview the other interview I nailed with the help of Raptor.
Hey OP,thanks for sharing your path to become a data analyst.So you recommend to ignore python for now and learn Sql and tableau/Power BI first right?And you think there are still entry level positions out there?I read companies are looking for more advanced Data analysts.I would love to hear your thoughts
Sorry for taking some time to reply Pete,
Raptor recommends familiarity with python or R for data analysts and proficiency for scientists/MLE. Also recommends to start as an analyst to build up experience/proficiency.
I thought I could skip that step and went hard into python to start, it would have been more efficient to just execute the in blog python/r coding (probably a month or so of work) then go hard at SQL, get the cert, start applying while simultaneously going hard at BI and getting the cert.
There’s definitely entry level positions. They might be contract/temp agency work (raptor would have better insight than me since I am just entering the industry) but they are there.
And raptor if I’m misrepresenting your views in any way, please correct me.
nope, your saying exactly what I would.
Thank you for the detailed response,I’m already half way there.
Great read.To become a data analyst,it’s best to only focus at the beginning on SQL,tableau or PowerBi only?no python?
Mandatory:
SQL
PowerBI/Tableau
Optional:
R/Python