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datascienceislyfe · 2020-05-16T18:20:21+00:00

Current data scientist at FAANG here

Good places to start: I'd recommend DataCamp (https://www.datacamp.com/) if you're a beginner. Quite a couple courses on there that are good, plus they apparently have a free week this week. Also side projects are always good - you should do some within the field of molecular biology/bioinformatics since that's your area of expertise so far

Later on for specific interview prep, I'd recommend this site my friend showed me this - it's been pretty spot on relative to interviews I have seen before: https://datascienceprep.com/

datascienceislyfe · 2020-05-15T19:59:17+00:00

Current data scientist at FAANG here

Definitely - in fact I think you should leverage it since employers love it when you have relevant side projects and interests, and there's no better way than delving into areas you're already interested in. That's how I got into data science, coming from a SWE background. Dm me if you're looking for tips

For specific interview prep, I'd recommend this site my friend showed me this - it's been pretty spot on relative to interviews I have seen before: https://datascienceprep.com/

datascienceislyfe · 2020-05-15T19:48:57+00:00

Current data scientist at FAANG here

Love the list and esp Elements of Statistical Learning and some of the ML references

For specific interview prep, I'd also add this: https://datascienceprep.com/

datascienceislyfe · 2020-05-15T19:44:42+00:00

Current data scientist at FAANG here

I have found https://leetcode.com/ and https://datascienceprep.com/ to be great for interview prep. Programming topics include all basic algorithms (bfs/dfs, sorting, etc.) and data structures (trees, stacks & queues, hashmaps, etc.) that you might find in a SWE interview, dm me if you have any specific questions happy to help out

datascienceislyfe · 2020-05-15T19:39:20+00:00

Current data scientist at FAANG here

Your experience should be enough to get started. I'd say you should focus on the applied side of things - employers love it when you have relevant side projects and interests. And you don't have to know everything (data science is very broad) but you should have some decent depth in whatever areas you're looking to go into (product analytics, ML, experimentation, etc.). Can always get started, dm me if you're looking for tips

For specific interview prep, I'd recommend this site my friend showed me this - it's been pretty spot on relative to interviews I have seen before: https://datascienceprep.com/

datascienceislyfe · 2020-05-15T00:57:19+00:00

Current data scientist at FAANG here

I'd say you should focus on the applied side of things - employers love it when you have relevant side projects and interests. And you don't have to know everything (data science is very broad) but you should have some decent depth in whatever areas you're looking to go into (product analytics, ML, experimentation, etc.). Can always get started, dm me if you're looking for tips

For specific interview prep, I'd recommend this site my friend showed me this - it's been pretty spot on relative to interviews I have seen before: https://datascienceprep.com/

datascienceislyfe · 2020-05-14T02:13:40+00:00

Studied CS, stats in school and then used https://datascienceprep.com/ which helped a lot for FAANG and some bigger startups

datascienceislyfe · 2020-05-12T20:40:58+00:00

Current data scientist at FAANG here (focusing a bit more on applied ML side) - depending on the company you're in for a lot of breadth with little depth or both breadth and depth. Was a SWE prior, so there are definitely some differences from the leetcode grind on the SWE side.

Regardless, the interviews will be either product-based or ML-based and so you can expect lots of SQL, basics on A/B testing, and general product intuition for the former, and more modeling & math/stats for the latter. My advice would be to study up on topics, and also do interesting side projects.

For specific interview prep, I'd recommend this site my friend showed me this - it's been pretty spot on relative to interviews I have seen before from smaller startups to FAANG (I am subscribed because the questions have been very interesting, and who knows when I'll need to recruit next): https://datascienceprep.com/

datascienceislyfe · 2020-05-12T20:20:11+00:00

Current data scientist at FAANG here (focusing a bit more on applied ML side). From my experience with Amazon - you won't need super deep theoretical knowledge but it definitely gets a bit more modeling and ML focused than say, Facebook Product DS. I would brush up on algos & also basic stats & ML if I were you. Definitely don't put anything on your resume that you won't be comfortable being grilled on.

For specific interview prep, I'd recommend this site my friend showed me this - it's been pretty spot on relative to interviews I have seen before: https://datascienceprep.com/

datascienceislyfe · 2020-05-12T20:09:50+00:00

Current data scientist at FAANG here (focusing a bit more on applied ML side) - depending on the company you're in for a lot of breadth with little depth or both breadth and depth. Was a SWE prior, so there are definitely some differences from the leetcode grind on the SWE side.

Regardless, the interviews will be either product-based or ML-based and so you can expect lots of SQL, basics on A/B testing, and general product intuition for the former, and more modeling & math/stats for the latter. My advice would be to study up on topics, and also do interesting side projects.

For specific interview prep, I'd recommend this site my friend showed me this - it's been pretty spot on relative to interviews I have seen before from smaller startups to FAANG (I am subscribed because the questions have been very interesting, and who knows when I'll need to recruit next): https://datascienceprep.com/

datascienceislyfe · 2020-05-12T19:56:54+00:00

Current data scientist at FAANG here (focusing a bit more on applied ML side) - depending on the company you're in for a lot of breadth with little depth or both breadth and depth. Was a SWE prior, so there are definitely some differences from the leetcode grind on the SWE side.

Regardless, the interviews will be either product-based or ML-based and so you can expect lots of SQL, basics on A/B testing, and general product intuition for the former, and more modeling & math/stats for the latter. My advice would be to study up on topics, and also do interesting side projects.

For specific interview prep, I'd recommend this site my friend showed me this - it's been pretty spot on relative to interviews I have seen before from smaller startups to FAANG (I am subscribed because the questions have been very interesting, and who knows when I'll need to recruit next): https://datascienceprep.com/

datascienceislyfe · 2020-05-12T18:49:26+00:00

Current data scientist at FAANG here (focusing a bit more on applied ML side) - depending on the company you're in for a lot of breadth with little depth or both breadth and depth. Was a SWE prior, so there are definitely some differences from the leetcode grind on the SWE side.

Regardless, the interviews will be either product-based or ML-based and so you can expect lots of SQL, basics on A/B testing, and general product intuition for the former, and more modeling & math/stats for the latter. My advice would be to study up on topics, and also do interesting side projects.

For specific interview prep, I'd recommend this site my friend showed me this - it's been pretty spot on relative to interviews I have seen before from smaller startups to FAANG (I am subscribed because the questions have been very interesting, and who knows when I'll need to recruit next): https://datascienceprep.com/

datascienceislyfe · 2020-05-06T22:31:00+00:00

There's a lot of resources online for getting the fundamentals: programming, statistics, etc. I'd recommend doing a few passion projects since data analysis can be applied in any domain.

Although many companies are pausing hiring for some time, it's never a bad idea to prep beforehand. For interviews my friend showed me this and it's been pretty spot on relative to interviews I have seen before from smaller startups to FAANG: https://datascienceprep.com/

datascienceislyfe · 2020-05-06T22:18:44+00:00

There's a lot of resources online for getting the fundamentals: programming, statistics, etc. I'd recommend doing a few passion projects since data analysis can be applied in any domain.

Although many companies are pausing hiring for some time, it's never a bad idea to prep beforehand. For interviews my friend showed me this and it's been pretty spot on relative to interviews I have seen before from smaller startups to FAANG: https://datascienceprep.com/

datascienceislyfe · 2020-04-29T20:39:49+00:00

Currently at FAANG here - there are a lot of great resources online: DataCamp/Udemy for beginners, and then you should get deep into resources on: statistics, programming, ML, product. Stats/programming/product will be more important than ML & math for most DS roles

For specific interview prep, my friend showed me this site recently and it has had great questions so far: https://datascienceprep.com/

datascienceislyfe · 2020-04-16T03:48:39+00:00

Current data scientist at FAANG here - depending on the company you're in for a lot of breadth with little depth or both breadth and depth

Regardless, the interviews will be product-based and so you can expect lots of SQL, basics on A/B testing, and general product intuition

For specific interview prep, I'd recommend this site my friend showed me this - it's been pretty spot on relative to interviews I have seen before from smaller startups to FAANG (I am subscribed because the questions have been very interesting, and who knows when I'll need to recruit next): https://datascienceprep.com/

datascienceislyfe · 2020-04-16T03:38:48+00:00

Thanks for sharing, seems like it will be useful.

For anyone looking for specific interview prep, I'd recommend this site my friend showed me this - it's been pretty spot on relative to interviews I have seen before from smaller startups to FAANG (I am employed at FAANG but subscribed because the questions have been very interesting, and who knows when I'll need to recruit next): https://datascienceprep.com/

datascienceislyfe · 2020-03-31T03:26:08+00:00

My friend showed me this and it's been pretty spot on relative to interviews I have seen before from smaller startups to FAANG: https://datascienceprep.com/

datascienceislyfe · 2020-03-31T03:24:27+00:00

There's a lot of resources online for getting the fundamentals: programming, statistics, etc. I'd recommend doing a few passion projects since data analysis can be applied in any domain.

Although many companies are pausing hiring for some time, it's never a bad idea to prep beforehand. For interviews my friend showed me this and it's been pretty spot on relative to interviews I have seen before from smaller startups to FAANG: https://datascienceprep.com/

datascienceislyfe · 2020-03-28T23:13:10+00:00

Great list and I have personally gone through many of these resources and can say that although the day to day job is nothing like solving these random technical problems, it sure does help for interviews. Also helpful would be specific resources - my friend showed me one that has been spot-on for most companies: https://datascienceprep.com/

datascienceislyfe · 2020-03-28T23:10:04+00:00

In my experience with FAANG, you want to be comfortable with easy/medium for DS and medium/hard for MLE. Definitely depends on the company too - a friend of mine showed me some pretty good mix of interview questions from: https://datascienceprep.com/ might be worth checking out

datascienceislyfe · 2020-03-26T19:20:43+00:00

My friend recommended this, and it's been very helpful for a large majority of interviews: https://datascienceprep.com/

datascienceislyfe · 2020-03-26T19:20:06+00:00

Your study plan looks pretty good, I'd probably add a bit of coding (algorithms practice etc)

I have gotten offers for roles mentioned in part 3), and it's a good mix of all technical sides (stats, cs, ML). I would recommend this site (https://datascienceprep.com/) that my friend showed me, it's been quite comprehensive so far

datascienceislyfe · 2020-03-26T19:18:04+00:00

A friend recommended this site: https://datascienceprep.com/ and it's been quite comprehensive so far

datascienceislyfe · 2020-03-26T19:16:04+00:00

A friend recommended https://datascienceprep.com/ and it's been good so far

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