Imposter Data Scientist wanting to become a MLE – what can I do to most benefit my career /u/Jealous-Diamond8750 CSCQ protests reddit

Hey there – I’m a self taught data scientist with 6 years of experience. My background is that I’ve worked in environments with a lot of moving things that need monitored, and I picked up python, studied statistics and deep learning and got to work. I’ve done a lot of fun math heavy stuff, ranging from training and deploying deep learning computer vision models to doing more traditional statistical analysis/machine learning with data to make business/operational decisions. I’m looking to start job hunting again, and I have a bit of imposter syndrome. Everything I’ve done, the entire “tech stack” is basically just python and some packages. I have no idea what an ETL pipeline is; I just write packages that upload data to S3 and then load it with some logic based on its prefix/key. I’ve never used anything like Apache Spark/Kafka, nor know what Hadoop, Kubenetes, or different types of databases are. I would love to learn about these things, but I don’t have a business case for why we should start using these things. Everything seems to be working without them – and I’m typically the only data scientist in my group. And so far, I’ve really only gotten jobs by word of mouth. E.g, someone I worked with says “Yeah, we had a camera watching this thing that would randomly go wrong, so we hired him to write something that would detect that and notify us, and they did. You should definitely hire them.”

Now, I’m interested in getting a role outside of where I may have contact, and when I look at job descriptions that ask for all these other things, I can’t help but worry about my suitability. I’m currently working in a role where I have a ton of free time. What can I do with my free time (~20 hrs a week) to benefit my career the most?

Hey there – I’m a self taught data scientist with 6 years of experience. My background is that I’ve worked in environments with a lot of moving things that need monitored, and I picked up python, studied statistics and deep learning and got to work. I’ve done a lot of fun math heavy stuff, ranging from training and deploying deep learning computer vision models to doing more traditional statistical analysis/machine learning with data to make business/operational decisions. I’m looking to start job hunting again, and I have a bit of imposter syndrome. Everything I’ve done, the entire “tech stack” is basically just python and some packages. I have no idea what an ETL pipeline is; I just write packages that upload data to S3 and then load it with some logic based on its prefix/key. I’ve never used anything like Apache Spark/Kafka, nor know what Hadoop, Kubenetes, or different types of databases are. I would love to learn about these things, but I don’t have a business case for why we should start using these things. Everything seems to be working without them – and I’m typically the only data scientist in my group. And so far, I’ve really only gotten jobs by word of mouth. E.g, someone I worked with says “Yeah, we had a camera watching this thing that would randomly go wrong, so we hired him to write something that would detect that and notify us, and they did. You should definitely hire them.”

Now, I’m interested in getting a role outside of where I may have contact, and when I look at job descriptions that ask for all these other things, I can’t help but worry about my suitability. I’m currently working in a role where I have a ton of free time. What can I do with my free time (~20 hrs a week) to benefit my career the most?