How to go from Data Science to ML/AI Engineering
I currently have 2.5 YoE as a data scientist for a large company. Job involves running ML algorithms on data sets after cleaning/sanitizing them and working with business stakeholders to find requirements/etc. In a profit center of the company right now working on building new implementations. I'm getting annoyed with the "70% of date science is clean-up" part and I want to do more SWE and coding. For example, the idea of building self driving cars or working on AI to launch shit into space sounds awesome. Starting master's in computer science with ML spec next spring with Georgia tech but don't really know how to get into the space now (as opposed to latter). Also taking deeplearning.ai course on Coursera to get up to speed on Tensor flow since I just use SKLEARN now. Also only know python but gonna learn other languages soon. Any advise appreciated! Thanks
deeplearning.ai
I was a DS at a non-tech company that also did critical backend work and did a lot of production ops. I applied for several ML eng jobs. Got auto rejected without any interview from most except one. Ended up getting that job. Luck is huge. Shoot your shot.
What got you auto rejected and how can I bolster my resume so that doesn't happen to me?
3+ YOE at a non tech company without a cs degree or masters or phd is probably why I got auto rejected. I managed to get into a FAANG now so I doubt that will be an issue again. Sometimes you just need that big break
how about starting coding more? making more production code, huh? build your ML models and then deploy them end-to-end, ok?
That's what I do. Doesn't mean I can get a job at Uber making self driving cars.
Software engineering skills are more important now if you already do ML as a data scientist. masters in ML will be useless. The only thing that may help is strong expertise in a particular domain, like vision/robotics/nlp if you want to get job in that domain. Not that many MS programs with domain specialization, but they exist.
Why do you think a masters will be useless? What do you recommend I do instead?
Masters in general ML will be useless, will not add a lot of credibility. Masters in specialized ML field can help. Are you good with general SC algorithms, data structures, complexity analysis. Coding and designing outside of python? If not, investing in it should be highest priority.
Majority of companies hiring "data science" just end up having you scrub data and no idea what supervised vs unsupervised learning is. Python, etc are the new buzzwords. Interview with a few companies and they're not even far along enough with their data pipelines or data collection mediums (e.g., loyalty card) to start serious analysis. The other issue is there is a serious shortage of talent so B player companies can't hire anyone.
I did exactly what you’re trying to do. Best thing you can do right now is automate the data cleanup and build a really good ETL engine from scratch. That’s how I did it
Data Clean-up isn't always so straight forward. For example, reading over documents to pull up important phrases of text for setting up ML models. We have lots of random projects which require unique solutions. Also we already have a full ETL time that handles all data loads and I admit I don't really know much about ETL other than ours works for putting large amounts of data into our DWH.
Lots of random projects, like 10? Automate one by one.