Goldman Sachs Analyst Interview Questions, Process, and Tips

Interview preparation tips for other job seekers - Read all financial markets related concepts and little information on advance Excel

Interview preparation tips for other job seekers - Prepare well as the test is hard to crack.

Round: Test
Experience: Mostly about maps
Duration: 1 hour
Total Questions: 3

Skills: Data Structures

Round: Group Discussion
Experience: I had a good time. Got to know new and valuable additions to Companies Act
Duration: 30 minutes

Round: HR Interview
Experience: It was a great exchange, I really expressed my views and visions well.

Round: Technical Interview
Experience: I was complimented for being calm, confident and patient throughout the interview.

Skills: Technical Knowledge(ML, Ability To Cope Up With Stress, Confidence
College Name: Maharani college

Round: Test
Experience: They had two rounds of test, one all objective and the other one all subjective. You had to clear a minimum cut off in the objective in order to get your subjective checked
Duration: 3 hours
Total Questions: 40

Round: Technical Interview
Experience: CV grilling, no hr questions

Round: Resume Shortlist
Experience: They shortlist around 300 resume from whole batch for next round.
Tips: Basically add your projects related to Machine Learning and coursework related to Math. GS is one of the companies which reviews resume carefully (At least I think so :P), reason being me selected even after a low CPI. Around 250 to 300 students were shortlisted from resume for second round.
GS is one of the rarest firms that will go through your resume thoroughly. Most important part is that GS is a firm you want to go for if you have a modest CPI and are genuinely interested in global markets.
They hire for Strats and Quants division. So highlight projects related to Natural Language Processing, Artificial Intelligence and Machine Learning Techniques. Mathematical coursework and internship in related field could be elaborated too. Even students with no internship experience whatsoever were selected due to their background in Machine Learning related coursework.
I have a little or no idea about programming division as it revolves around networking and related projects.

Round: Test
Experience: They started hosting test online on hackerrank. It includes three sections with equal weightage to each of them. You have 45 minutes for individual sections. There are three type of questions asked - MCQ (+10, -3), Fill in the blanks (Numbers upto 2 decimal places; +10, -0) and 2 coding questions in programming section (+20, -0).
Programming - 2 coding questions. Questions about networking, cache and DSA (postfix and prefix expression from stack related algorithms).
Quant - Cattle grazing the circular field tied from a pole at the corner of a rectangular shade with a rope. Some about practical probability problem of die throws. Other about matrices and determinant. Theoretical questions in probability covers a major portion in form of expected value, correlation and covariance calculations. This section had some integer type questions.
Data Sciences - MLT theory should be a stronghold. Particularly confusing theoretical questions. Some of them had 4 statements and then 4 options asking correct statements so you have to be good at multiple topics. Typical question include possible solution to account for missing input data and regularization among others.
Tips: You have to be good at any two of the sections. Quant is quite competitive as the questions are easier and CSE guys can attempt these too from mathematical coursework on prob and stats. Typically whole batch is rooting for this profile because of lesser chance in CS related profile.
A little brushing up old DS notes won't hurt anyone. Specially tree, graphs (algorithms like Bellman Ford, Djikstra and Prim's algo), complexity of standard algorithms and postfix, prefix expression derivation will help a long way. Coding questions demand efficient solution, otherwise you won't be able to clear all test cases because of TLE.
For quant, Prob Stats and Linear Algebra course review is highly recommended. A little aptitude (CAT related although a lot higher standard than that) will help too.
In data sciences, ML lectures will help a lot as most part is theoretical which can be solved if you have your concepts strong. Gaussian distribution, Regularizer, PCA are some of the topics which were asked about.
Duration: 2 hours 15 minutes

Round: Technical Interview
Experience: At first I couldn

Round: Resume Shortlist
Experience: The resume shortlist, I feel, was slightly unfair. They had put a cut-off of 9 for branches outside EE/CS.
Tips: Don't worry, they might not follow this next year. Your resume should have a mix of probability, finance (courses on these are enough, though internships will really help)

They don't care about your PoRs in the interview, but this may matter for the resume shortlist (Assuming it's done fairly) So be sure to include them.

Round: Test
Experience: There were 30 MCQ questions, 10 each on the above mentioned sections. There is no dearth of time, so you can think clearly and solve the question. I found that quant was the hardest of the lot, followed by coding followed by ML.

ML questions will be on SVMs, ANNs, Ensemble learning methods, Hypothesis testing, Feature selection, Model selection etc. the standard topics you can find in "Elements of Statistical Learning" by Hastie, Tibshirani and Friedman.

The coding section was mostly on arrays, data structures (binary tree, mostly), recursion, and one subjective question.

For quant, you need to be really well versed in probability, definite integrals (Not kidding), and other JEE math.
Tips: You'll need to do really well in atleast one of the sections to be shortlisted. Even if you are non CS/EE, (assuming you don't have experience in coding) you can do really well in ML section. Aim for that and prepare in advance. Once you are through to the interview, you just need to give them a reason to hire you. :)
Duration: 2 hours 15 minutes
Total Questions: 30

Round: Technical Interview
Experience: The lady who interviewed me was a chemE graduate from IIT Bombay. She was friendly and willing to help when asked about a problem. Overall, very good interview experience.
Tips: For all interviews, I'll say this. Ask a lot of questions. They are very interested in explaining what they do, and feel free to interrupt them if you don't understand something. Always try to relate what they say to your interest. That way you'll bring new perspective into the interview. And that's very useful, believe me. If they have shortlisted you, they want to hire you. You just have to give them a reason to. Always relate your experiences and your interests with what they do. if you do that, they will find a role for you, somewhere. Do not worry. I was interested in machine learning and I got a finance profile. (They have a team in that profile that does ML)

For quant questions, I would suggest thinking out loud and interacting each step of the way. They care more about your thinking than about the answer. They will point out the errors and you can correct them. Don't worry about silences, as long as you think out loud, it will not be a problem.

Round: Technical Interview
Experience: Again, very friendly interview. The interviewer will lead you on, and assist you if you're facing any difficulty. :) Just be sure to be jovial and interactive.
Tips: Same as above.

Round: Technical Interview
Experience: Very technical, serious interview. I think he was the senior guy. He still helped out a lot.
Tips: Be to the point, he was more interested in the technical knowledge.

Round: Technical Interview
Experience: The final interview I had. He was very helpful, and was very eager to talk about the company and what they do. He had an extensive knowledge of finance, options (obviously). The course on Mathematical Finance by the maths department was very useful. You need to have a good knowledge of options for getting through this.
Tips: Same as the first interview.

Skills: Quant+Math, Problem Solving Abilties, Probabiity, Internship Experience, Finance
College Name: IIT Madras

Round: Technical Interview
Experience: Talked about probability and programming questions. The same happened in 4 rounds of interviews.
Tips: Prepare probability and quant questions. Be calm. The interviewers are very helpful.

Skills: Probability And Statistics, Programming
College Name: IIT Madras