Google research scientist interview reddit Let’s get into the four primary categories of questions you’ll answer during the Google data science interview: Statistics and Machine Learning (56% of reported questions) Coding (26%) Behavioral (9%) Product Sense (9%) Note that many of these questions are asked in the form of case studies. Research scientists might be asked some of this, but you are right, DL interviews are more based on deep-dives into your past projects + research (rather than some nuances around Q-learning). For Facebook, I got the interview request within a few days, while for Amazon, it took a few months, so that can vary widely. Now, for title "applied scientist" or "data scientist", you will probably be expected to produce new models. I also dread seeing leetcode because I frankly suck at them but I can see how asking them can be useful to interviewers. I stumbled through the second interview and approached it incorrectly at first, rerouted, and finally solved it with a hint from the interviewer. How to Prepare for a Machine Learning Interview. The Google DeepMind Data Science interview process typically takes 4–6 weeks to complete. I would suggest you just apply, it is possible you get a referral with people you don't really know much, but it is unlikely. Hello everyone, so I recently interviewed for Meta / Facebook (research scientist intern US office), I had 2 virtual on-site rounds: . That's why when I interview folks, I don't worry too much about Tech skills honestly). In that company, the applied scientist role is actually the top position for scientists. The process includes: Initial Recruiter Screening. for Product Data Science roles, I like Trustworthy Online Experiments since open-ended questions about A/B Testing and Hi all, I have a couple of interviews coming up for research scientist roles with FAANG-like companies and since it's my first time going through this process (finishing grad school, never applied to industry positions before) I was wondering how the interviews are conducted and what they look at the most. If your interviews are spaced by like 5-7 days - that's super easy to accomplish - it just takes some discipline arguably. Most data science positions are not at Google or top tech companies. We would like to show you a description here but the site won’t allow us. Both were pretty much like poster sessions -- they asked me to talk about some of my recent papers, then asked some follow-up questions. I was curious about the kind of questions that are asked in an interviews for AI/DL Research Scientist (or similar) positions in top tech companies like FAANG (but not limited to, of course). Note: I’m at Amazon. Stuff I’ve Messed Up While Interviewing. Google is way ahead other companies in the AL/ML field. Google did invent the leetcode-like interviews (e. The research scientist role is for people that are weaker at software engineering (sometimes people that don't do well in the coding interview are offered a research scientist role). I was quite shocked at how thorough I had my research intern interviews last week. The process consists of roughly 5 distinct stages: Recruiter Screen; Technical Coding Interview(s) Technical ML Interview(s) Hiring Manager Interview; Cultural Fit Interview EDA/simple modeling coding interviews aren’t common in my experience for data roles, usually the coding interview is just some form of leet code. I do some of the technical interviews for a data science team at a fortune 100 company (not FAANG), and we usually have a PM in the room who will ask you “what’s your biggest weakness” type questions, and if you say something like “oh I work too hard,” it won’t look good. Then continued down the Meta top tagged list. I eventually got the Google position through a referral from a Google Research Scientist I met at a virtual conference. Applied scientists must meet both the SDE bar in the interview on top of the data science elements. It’s a very hard role to fill. There are a lot of insurance companies and financial institutions and others that use data science as well, and they may use these questions in the first interview. We don't force interviewers to follow the exact same time breakdown, but the following is typical: The first 5 minutes will be a mutual introduction The next 35 minutes will be one or more coding problems We try to reserve the final 5 minutes for your questions for the interviewer. It was really easy to get high-paying ML jobs after leaving Google. Applied scientists are the highest paid IC family. To go fast one must go slow. Mar 10, 2025 · Got a interview for Google on the DeepMind team for a Tech Program Manager role focused on AI research. Interview timing Your interview will be about 45 minutes long. Google AI looks great on resume. reddit's new API changes kill third party apps that offer accessibility features, mod tools, and other features not found in the first party app. I took some notes on the types of questions that they asked. Crushed it: Landing a data science job. Nov 11, 2024 · 32 Google Research Scientist interview questions and 33 interview reviews. Even finding people to pass the DS bar is hard. The system design interview was hard, but mainly because how open ended they are. For Research Engineers. At google theres a good chance it will be a standard software engineer interview unless you are special (real experience not just education). more so popularized them than inventing. While I only interviewed at DeepMind and Google AI, I expect this article to apply to many other research scientist internship (or even research engineering) programs, as well. The research interviews will be other research engineers asking you about your previous research history. Mar 2, 2025 · Explore expert strategies for tackling Google research scientist interview questions—ideal guidance for aspiring candidates, offering insights, and more. There are very few true research positions except for at big companies in specific teams: Google Brain, Meta's FAIR, OpenAI, Samsung Research, Microsoft Research, etc. It was very senerio driven. On the data science side solving difficult problems takes months, not hours, and pushing someone reduces that necessary creative aspect. . Google interviews are notorious for being difficult, so take these few weeks to practice! Try to keep your mental state easy (eg, don’t get too stressed or aroused), and approach the interview with a learning-mindset (instead of needing to ace each problem) As a research scientist and former research scientist intern I can highly recommend the internship for all current PhD students. I could, however, do some reading and be up to speed within a few hours. Let’s walk through them. Day to day ML work is more about data/model/result interpretation, building hypothesis for next set of experiments, and coding up pipelines rather than using BFS/DFS and dynamic programming. For the average ML engineer, the interview process is still LeetCode heavy, with some more basic stats + classical ML questions thrown in, along with some The technical questions are more basic and easy. Hahah thanks! It's more like paper skimming TBH. ) May 21, 2024 · Google Data Scientist Example Questions↑. I've heard people got 2x salary from other big corps last year. I like both roles but I am leaning towards Google (not sure if they will negotiate working from the ATL CSCareerQuestions protests in solidarity with the developers who made third party reddit apps. I tried finding online but could only get some vague answer without specifics. Free interview details posted anonymously by Google interview candidates. I am a freshly graduate student from a tier-3 university ( In India) with a Computer Science Engineering degree and I got placed at a start-up (now MNC) with a Data Scientist role ( Although my job will start from Jan, they delayed it citing the recession, it was a startup when I got the job but between the time aquisition happened and it got under an MNC) There you're expected to give a talk about your research (45 min + 15 for questions), followed by a full day of interviews. Steps to Ace Hi! Thank you for your answer. Jul 25, 2023 · It's worth distinguishing two confusing AI title differences at Facebook. For the data science theory part, I basically memorized "An Introduction to Statistical Learning" (published by Springer) and was very strong. I did two interviews, each with a different researcher. With Google salary you can live like a king even in Zurich. My experience and interview preparation below. Chip Hyun's free Machine Learning Interviews Github Book is great for ML Engineering or Research Scientist/Applied ML Research roles this Data Science Interview cheat sheet is a great way to get a survey of topics covered. Feb 24, 2025 · The data scientist interview process at Google is standardized and similar to that of many other tech companies. He was slow to respond, and I often had to email multiple times just to get a response, but my perseverance paid off in the end. I spent 30 minutes completing their application form, repeating things that were evidenced on my CV - this was on 25th September, I then received a rejection email - all very generic: We appreciate your interest and the time you took to apply for the Talent Acquisition Partner, Research & Science - 12 month Fixed Term Contract role here at Google DeepMind. Interview with Microsoft was a very standard Data Scientist interview process consisting of coding round, ML theory round and Resume based round. Also, I have another interview with BCG for a Tech Advisory Manager role located in Atlanta, GA. There is some ML, some A/B testing but not much. It sure helps to have a lot of publications under your belt but the hiring process for the research scientist positions still involve technical interviews where your knowledge of data structures and algorithms are tested (which is often not a part of the hiring process in academia). Pushing for speed is going to get you young inexperienced data scientists or desperate data scientists. Just do some behavioral interview question flashcards. Sounds good. Six months later I failed the final round of a fb data scientist interview. There are Research Scientists within Facebook and then there are Research Scientists at FAIR. For MLE I had an initial can with the recruiter, tech screen (2 Leetcode style questions) and a final round with ml system design, leadership/behavior, more coding questions (I had 2 2 round sessions) and Got interested in data science in 3rd year of college, did a lot of MOOCs on Coursera and applied off-campus in 50+ companies to land a job in Amex. Google X was purely past research experience and ML knowledge. Do you mind giving a little bit more details about the role? How involved in research are REs or is it mostly running experiments for research scientists? How is the environment generally between REs and RS? Do you have any pointers about the interview process? I would appreciate your help! I'm sure i did well but the uncertainty is KILLING me. Interviewer for Google here. Facebook's interview was better. Mar 19, 2025 · How shall I get my application shortlisted for an Applied Scientist/Research Scientist/Research Engineer role at Meta, Google or Microsoft. They would give you different types of business senerios that require you to form an analytical approach. Ask anyone who reads papers regularly - you could skim-read 3-4 papers daily no probs! Especially once you become proficient with paper reading. Here are some notes: Google interview questions: Second though, there are two types of Data Science roles. I recently interviewed with a faang for Applied Data Scientist and it went like this: 1x ML interview 3x Leetcode interviews 1x high level system design interview How important is leetcode to the actual job of ML / DS practitioners? Is it that important to have 3 leetcode problems vs 1 ml problem? So in this article, I want to give a short overview of how I approached the interviews, focusing particularly on preparation and less so on the exact process and timing. The position is in Mountain View, CA. I’d probably fail your “interview”. They might contact you soon. Applied scientists may even be expected to know more in their field. The process starts with a call from a recruiter, who reviews your CV and verifies the details of your technical expertise and interest in Google’s data science teams. I'd suggest that you accept the other offer and if Google reaches you, you can let them know about the other offer and go on with the interview with Google. Common Probability Distributions: The Data Scientist’s Crib Sheet. Don't know what a research engineer interview looks like, but the mle (swe ml) interview and research scientist interview are very different. Data Science Interview Questions with Answers (discussed) How to Ace Data Science Interviews: Statistics. The 1st was a research/team-match interview:(3 Dec) I think I did good in this interview, as the interviewer seemed happy and told me at the end I learned a lot from you and I wish you lucketc, so he seemed happy and the conversation was very nice. g, the algorithms and data structures trivia); well. This is why whiteboard problems are frowned upon for data science interviews. I correctly answered the first interview question and explained my thought process/pseudo code for the follow up before running out of time. I also spent eight years at Google, where I worked on pose estimation and 3D vision for StreetView and developed computer vision systems for annotating Google Photos. FAIR Research Scientists focus on producing groundbreaking research and publishing papers - they are the equivalent of Research Scientists at Google. When you say leetcode-like do you mean whiteboard data structure / algorithm problems? Not Google, but when I interviewed for Amazon & Meta (then Facebook)'s data science internship positions, there were 2~3 rounds of interviews, so I imagine it's similar for Google. It seems that DMG is pretty independent and their interview process is different than regular DeepMind. Asking specific, hyper-technical questions during interviews is a recipe for disaster. So yes. Data Science Interviews. I'd hire people from Google AI if I were hiring. I reached out to the recruiter the day after my interview and he said 2/3 interviews had reported back so i was just waiting on the one. I'm a 3rd year PhD student in a well-known research group at a well-known school with publications at top conferences, and I was also mostly asked basic ML questions what the softmax function is, what are the potential computational issues in practice, and (1) Interview w/a research scientist (2) Loop interviews - Presentation - Behavioral (typical questions like, how do you deal with difficult people) - Technical interview (explain a project you worked on, and then a lot of methods questions, like how do you select sample size, etc. Specifically, the recruiter said that there'd be a coding/code review round at the 3rd stage I also applied for a student research internship at Google in Sept 2022 and just received an email inviting me for an interview. Apr 11, 2024 · How shall I get my application shortlisted for an Applied Scientist/Research Scientist/Research Engineer role at Meta, Google or Microsoft. I have an interview for a DS position with Amazon this Wednesday that I probably won't take because I will be accepting an offer from a start up. While this blog post is not strictly about ML research, I thought it is an interesting read because it is written by a senior research scientist at Google Brain. Moral of the story is to keep your head up! A little under 200 before first screening. Simply applying on portal do not helps? I also try writing cold emails to hiring managers, if they share opening on linkedin? My profile is good with papers published in top tier conferences like ACL, EMNLP. At my current company we actually do EDA/modeling interviews for data roles, but we try to keep the scope very focused, and overall the exercise takes 20m. Finding candidates that can pass the interview is very difficult. I haven’t used or studied decision trees in like 7 years and yet I’m a data science manager with almost a decade of progressive experience. I had an on-site interview at the Google campus about a year ago for a data science position. It's a lot of SQL, dashboards, creating metrics to track the success of projects. Hahah! disclaimer: I work in FAANG I feel the swe interview process is totally leetcode oriented rather than actual ML problem solving. I've set a lofty goal for myself for 2025 to be competent enough to interview at DeepMind/Anthropic etc (not to work on LLMs or the current trendy topics, but maybe general Research Engineer types), with an emphasis on both solid understanding of the fundamentals and cutting edge work being done in the field. Mar 27, 2025 · Awful. And you might just end up doing general software engineering. The most common type (mine) are really glorified Data Analysts. Typically a screening then 5 rounds, if you know someone and have a good referral they will skip the phone screen. If you interview for a research role at Meta - you’re likely to have 6-8 interviews. The process will likely start with a screening interview with the hiring manager (usually a discussion of your research), followed by 6 “on-site” interviews (these may happen virtually despite the term “on-site”), and a 1-hour research talk. There are certain things you can do to properly prepare for an interview. I see lots of interviewing details shared for DeepMind, but none for DeepMind for Google (DMG). Note that there is currently a hiring freeze for Google in Europe. Probably reflects what Google thinks about the culture of their research divisions, how they perceive engineering vs research, and who they may want to hire. Couple brainstorming questions. I heard that there's changes on the interview process for RE at Deepmind since last year, but I couldn't find the details on glassdoor or blind. I did my interview on the 16th and i know for sure at least 2/3 interviewers love me but havent had a change in status or update from recruiter. Those interviews will be some combination of coding and research interviews. Hey, I got contacted by a recruiter from Reality Labs for a UK based team there and so did a bit of research about the group and the interview process etc but what I found along the way are salaries that are let's say underwhelming. Then revisited some of the harder mediums and the non-dynamic programming hards, because I in fact learned later that Meta apparently does NOT (or is not supposed to) ask them. Absolutely awful. As far as I know, this is the standard for Google PhD Research internship interviews. The computer vision team I lead at Google invented the Inception neural network architecture and the SSD detector, which helped us win the Imagenet 2014 Classification and Yes, interviews are still mostly leetcode. So far from the US salaries. You'll probably have to fight to get one of these positions, because the headcount isn't high. 6 months later brings us to today. Usually around 100k pound for software engineers at Meta according to some sources. Dec 17, 2023 · Google DeepMind Data Science Interview Stages & Timeline. **Reddit Band Directors** is a place for middle school, high school, and university band directors to meet and discuss the profession, instructional strategies, band literature, and other issues! 1) Be helpful, provide insight, and do not be judgemental and/or flame other users 2) No trolls 3) Comments must stay on topic 4) Have fun, and spread Hi, I've gotten an interview for the Research Engineer (NLP) role at Deepmind and am prepping for the technical interviews. xjzppyhjdvphxxpozjwrhbjqgbvjtuebizwgslakufwbspondzrfikpodvqayyphwbrcyoenjlujubuhwi