How to Prepare for Amazon Leadership Principle Questions (6 Steps) (Purdue MS Business Analytics Grad POV) - w/ Samridhi transcript

Everybody tells you to apply to more jobs. She applied to fewer and walked into Amazon in the worst job market in a decade. I made sure I do not touch them unless I had more than 50% similarity with the job description. Samridhi Vats Purdue business analytics batch of 2024 started as a business analyst at Amazon. now a business intelligence engineer and at this stage make sure you're not using any AI or any uh tool to refine what you're writing. Use it as your dumping ground to dunk everything that you have done. That's step two of six. Here's the one people skip. Data points are very very important for leadership principle questions while you're explaining and and Amazon likes to pure data points and 2 years in the job itself has changed. Every one of us have our own personal agents to work upon and also

team based agents. We all know, you know, how to work with different MCPs and all of that. It's not a secret to us anymore. It's not just for developers anymore. anymore. Here's the whole Amazon system start to finish. Please join me in welcoming Samridhi to the Ready Set Do podcast. Let's go. Samridhi, welcome. Thank you. Thank you so much, Nam, for inviting me to your podcast. I'm excited for our conversation today.

Me too. me to what I wanted to jump off with here today is um the Purdue business analytics course and just all the really diverse opportunities it seems to unlock. So obviously both of us went to Purdue a lot of my friends were from business analytics and way more so than any other degree even outside of Purdue right like any other master's degree I just am forever shocked by just how many doors the business analytics door or the course opens for students. So what I wanted to jump off here with um was that you obviously started off at Amazon as business analyst too right after your graduation. Take us through the course itself and in what ways if any it set you up to land that position at Amazon.

Mhm. Yes. Um I would 100% agree to your point on um the course being so diverse and it kind of prepares you for different career paths and opening doors for different career paths. for me um when I started the course or when I when I landed into the US uh and of course in in Indiana for Purdue University's degree um I came up I did not really come up with a lot of expectations on how this course would um carry forward what it would lead up to or uh what you know career path it would prepare me for but going inside the course uh it at least gave me uh multiple options. It opened my eyes to multiple options that can exist for someone who is in the analytics path or someone who is in the data path starting from data analyst, business analyst, data scientist, machine learning engineer, AI engineer, solutions

architect, um or if you want to go more into the business side or management side, a lot of the management consulting uh kind of roles as well because of right balance of courses. It had uh for us at least it was a one-year program um with 36 credits to complete and a lot of courses to ramp up in one year and we had certain technical courses which were mandatory to complete certain business courses that were mandatory to complete.

Uh so I felt like one advantage of the program was that it was not too lopsided on one aspect like too heavy on technical or too heavy on management. It was a good mix of offering strategy courses as well as the technical courses. Um for example all the from introduction to SQL to advanced SQL the basics of business analytics to advanced business analytics uh which covers you know all your statistics and forecasting and everything and then as well as the management courses in terms of understanding the business strategy, marketing management, competitive strategy all of that. So it gave students the option to choose and then kind of pick and select courses to build their career path. Uh if you wanted to pursue the path of a data scientist, you can choose these courses. Um obviously there were some mandatory courses and

then you can add on to your optional subjects that you want to take on the electives and um so that freedom and that uh options of different courses kind of um gave me exposure to multiple courses and prepared me for uh different parts. I was ready to take up roles in data science space as well. I was ready to take up roles in um analytics space as well. of course uh given my interest in the field and if I'm if I would have been interested I would be open for for um job roles in management field as well like you know management consulting with the analytics part added to it. So um I guess yeah the the multiple options that we got in terms of courses um each courses came up with the practical projects. Um in the in the spring semester we had industry practicum where we get to work with a real company. um

they offer us projects and we get to work with those people directly see how we can solve their problem uh create an impact there get involved in multiple hackathons competitions so all of that combined kind of shapes you to for your transition to the industry or whichever field you want to go into the industry. So all of that combined kind of helps you build your profile. Yeah. sure if I answered your question but but no you did you did and I guess where I'm trying to go to next is there's been a lot of talk especially of late around the business analyst course becoming almost way too broad especially for international students to meaningfully look at in terms of you know like let's say somebody comes let's say somebody starting their masters today that is trying to you know get hired eventually for business analyst courses and I don't

know if this is your experience as well. But from at least the online spaces that I lurk in, there seems to be a rising consensus that it's not just enough to train or you know upskill oneself to be a business analyst anymore. Like you need to be more niche is what some people say. Some people recommend going towards data more. So like more data engineer type positions. So obviously you you are at least I know you started off and you've changed your position since but you at least started off as a business analyst at a big tech company.

So I do want to pick your brain around how you approached upskilling for that. Um and whether through your you know hiring process or job application process you found or you know you came across any signals that indicated either for or against the traditional business analyst no longer being an option especially for international students. Yeah. Um I I agree and I know there's a debate right now with being a generalist or an expert specialist in the field.

Given the given the pace at which the technology is changing right now because of AI the roles are becoming blurry. A lot of the roles have similar uh job duties uh despite having distinct responsibilities on paper. In real world people are doing almost similar jobs. So there's a lot of overlap and things are becoming blurry. Um and same is the case for business analyst. On paper this role might not sound as technical uh but in reality at least in a lot of the companies or people I have interacted with it has become much more technical than it is supposed to be I would say or it is understood to be. Um like from for me personally I would come to your question of upskilling in a bit but for me personally as well right from the time I had started in Amazon in my role it was never really a uh non-technical work per

se I was always doing the work for in terms of you know writing the queries or building the uh pipelines or uh doing all those work in ter at the back end to prepare the data well for the insights and all of that. So having said that when I talk about how I uh focused on upskilling or identifying those signals for my profile um one thing I recognized was the foundations for a business analyst, data analyst, business intelligence engineer.

Uh these kind of roles are similar. you need to have a really good understanding of uh quer like quering the data any quering language primarily SQL SQL so uh so yeah primary SQL or Python if if your company prefers to do like you need to know how to do data wrangling with Python knowing numpy pandas at least all of that not going into the advanced uh programming with python but definitely data wrangling using numpy pandas mad plot li but at least SQL if not Python.

Uh I recognize that this was a mandatory language to know uh be it you are interviewing for a data analyst, business analyst or any role in the analytics field. So having identified that I kind of upskilled myself or learned um SQL at writing queries all the all the logics of SQL all the functions and all of that. So I kind of made sure I'm good at that part and my foundations are right. Um the course had through different courses we took at Purdue that had eventually prepared me in multiple other aspects as well. You know uh Python we we learned that through multiple projects and courses.

Um statistics you should also be really good with u statistics understanding how different different principles in statistics work. hypothesis testing all of that even that is quite relevant in the in this space. So um so I would say SQL statistics um and then the stakeholder management the ability to transition your uh findings from the data into insights that can be taken to the stakeholders so that that can be taken um to the business question you were solving for and it can answer those questions. So that ability that just writing the query and getting the data output is not really useful. You need to know what to use from that output, what to get from that output. So um I would say if I would lay out the the foundational skills it would be uh SQL or any quering language, understanding of statistics, uh

understanding of turning those uh data output into actionable insights and then stakeholder management because you need to communicate that to the um stakeholders you were working with. Yeah. So, yeah, that's super helpful. And I know when you first got hired, it was a particularly difficult time just in the job market. If anything, it's since gotten worse somehow, which is surprising and also sad, but it was already pretty bad when you uh probably landed your position. So, I am curious if you can maybe share a little bit about what that job surge was like for you in terms of, you know, just your general strategy. Were you more targeted or more spray and prey? Usually it's one of the two approaches that people pick and then once you do that I'm also curious to uh explore the hiring process itself or like the interview process for

the business analyst position or at least the business analyst too at Amazon. Amazon. Yeah. Um for sure. So for my job strategy, strategy, it it was I graduated in um in August 2024. So kind of from March 2024 onwards, we were into the mindset of job hunting and job searching because you're graduating in August. Um as you said, the market was brutal and has gotten worse uh since then, which is not a good sign. But um for me my job strategy was targeted as you say. I uh I knew that if I apply to any job that I come across that would just increase the volume for me and not really kind of add quality to that volume. Mhm.

So um my strategy was uh sticking to the job descriptions that meet my requirements and the uh the job descriptions whose requirements I meet. Uh I did not want it to go beyond what they you know expected like if they had a list of things that they expected in someone's experience u knowing you know 10 different languages or having worked in different domains than I had. I made sure I did not touch them uh unless I had more than 50% similarity with the job description. So because it was just waste of time and effort to apply that just here just for hearing rejections. So couple of things I followed was uh making sure I stick to the number of years requirement. uh coming from India I had like two years of work experience and most of the companies look for full-time work experience uh and not really count the internships and all of

that. So I made sure I did not apply to companies who are looking for you know five plus years uh you know six plus five plus or sometimes four plus years. uh why am I saying this is a lot of the students do apply in the you know in the rush of just applying in volumes and making sure that their application is spread out uh in the market they kind of touched those domains as well where they do not meet the requirement. So I made sure I uh I applied only to where I met the criterias and all of that. Um and besides just applying from the usual job boards like LinkedIn or other websites which post jobs on a regular basis um I remember I used LinkedIn extensively. I also connected with a lot of people that time uh who are you analyze mentors and um kind of took feedback from them or understood tips and tricks. So I got to

know from one of them that there are a lot of uh websites that posts about startups who got who have gotten their early stage who are in the early stage have gotten their funding and all of that. There are a lot of venture capital websites which lists all the web uh all the startups they fund in. So that will give you a list of website um which has companies you can probably go and check their career pages and all of that. So I kind of amplified uh my uh scope by trying different job boards, different um uh job boards other than the traditional ones on LinkedIn as well. I I had premium that time. I made sure I sent connections to I used to add like hashtag hiring # reccruiters # hiring managers all of those keywords which are relevant to my profile on LinkedIn and then every people who showed up um on the list I would connect

to each of them um like I used to exhaust I think there's a limit of 100 connections per week so I used to exhaust that and I had a sample message drafted for each of the connections and a sample follow-up message as well. So I used to use that. I used to customize my messages for some of the profiles which were like a really good fit for my role I'm looking in. Um so so how that helped me is I definitely did not get a lot of um opportunities from them directly in my DMs but since I added them in my network and they were my first connections if they made any hiring post that came to me sooner than otherwise it would.

Yeah. So these were like few uh tips and tricks I would say I did other than what people usually do in terms of flying through job boards and um um yeah so these are the few things that I would I would say that I did in my job hunt strategy. strategy. Got it. And then so how did the Amazon opportunity come to be? Was that through a DM or did you just cold apply? How how did you hear back? Cold application. That was through a cold application. Did you do a referral or was it just purely cold?

Uh this was for for a referral is uh the role that I'm currently in. I did get a referral for that. Um and I had applied to again a lot of roles at Amazon and most of the business analyst two roles uh which are internally called L5 business analyst two roles um had a requirement of three plus years of work experience after your uh masters or bachelors. Uh thankfully the role that I got in for uh the current role and I got the referral for that uh that one had two years plus requirement. So I met the criteria and that's why I went ahead I could go ahead with uh this one. All the other roles had three plus years of requirement and um my prior experience in India was only for two years. So I was not meeting the criteria.

So that's another thing that's why I say to stick to the requirements especially for the big tech because if you do not meet their uh number of years of experience requirement or some other requirements the bot tends to reject those applications a lot. Yeah. Yeah. So um Got it. Yeah. And in terms of the rounds themselves, like I know Amazon is super heavy with behavioral rounds. So was that your experience as well? Can you maybe for somebody that you know is shortlisted or is trying to prepare for the L5 uh BA2 role? What what are some must check boxes that each candidate must you know really be looking at? Yeah. Um so for BA2 role there were primarily two distinct rounds. First round is a phone interview. It's a technical round per se where you are asked SQL questions uh some product case study type questions um asking basic

statistics like hypothesis testing different types of testing and all of that. And for SQL queries you need to uh write queries. You might not have to run them all the time like it might not have a compiler at the back end. You just have to whiteboard it. But uh first round is purely technical with SQL follow-up questions on your SQL on how to optimize your query and all of that followed by one or two leadership principle questions or like behavioral questions as as uh it's said commonly. Mhm. Mhm. If you clear that round. Yeah. Sorry. No. No. Yeah. I was you keep going. Yeah.

Yeah. So, uh once you clear that round, the second round is a loop interview which is composed of five rounds mostly. I have heard for some people it it was six rounds but mostly it's five rounds that what I have heard. Um each round is an hour long round. One of that would again be a technical and a behavioral mix. uh with technical being the query writing or the SQL testing part and uh one or two behavioral questions and the remaining four hours or the four other rounds would be your behavioral rounds which are all Amazon leadership principle questions would be asked in those rounds. Got it. And then specifically for preparing for the Amazon leadership questions do you so a lot of people prescribe a lot of things. So on this podcast I've had let me count here it's becoming a lot like you know an Amazon

road show at this point but I've had two DPMs another I think he was a business analyst also. So basically I've had a bunch of people from Amazon and what's really interesting for me is that they all have completely different strategies to you know prepare for the the leadership principle type questions. So curious what your you know personally for you how you approached to prepare for those because that's the only thing that you're guaranteed like you you know you're definitely going to be asked those questions. So how did you go about preparing for them? Yeah, that's a important question also um often asked question to me as well on how to prepare rounds. Now you can just point folks to this episode once it drops and you don't have to answer all of them. Yeah, I tried doing that like I had jotted down

my method of doing and and shared on LinkedIn but uh I would love to share my strategy and I feel like it it really worked for me and I u advertise that to people that you should follow that it would work for you. So um there are a couple of steps first is obviously to understand all the leadership principles uh what they are. There are ample resources online by Amazon itself. There are documents and videos by the leaders explaining what what each uh leadership principles need. Once you understand that, first step would be take a paper or like go on your laptop uh open a word document and then start writing down all the projects that you have worked upon. you can refer your uh you know different sources like if it's from a work project you can refer your old résumés or any documents if it's academic project you can refer your

results and uh start jotting down so at this point uh this is the most important point it's like data gathering stage where you just scout all your resources that you have worked upon be it your uh course project internships your previous job experience or your uh any competition or hackathon projects. Write everything down. Start with just writing the keywords um and then some description about it. And at this stage, make sure you're not using any AI or any uh tool to refine what you're writing.

Use it as your dumping ground to dump everything that you have done. And do not think which one is important, which one is not. not apply any filter at that stage. Just dumb down everything. Now the next step would be on each of the project that you have listed add the details what you did what was the outcome what tools you used. Again no structure at this point just write down all the details for each projects that you have listed. If you have to uh reach out to your old colleagues or your teammates or something, do that but collect all the resources that you need in case you forgot and have them written down on that uh on that document. The next step comes applying structure to that. So each project that you have listed make sure the description is in a star format or it fits the requirements of a star format. like it has the

situation component, it has the task, it has what actions you took, what tools you used, it has the results, it has the data points, um data points are very very important for leadership principle questions while you're explaining and and Amazon likes to hear data points. So at this stage once you have added all the details applied a structure to your projects the next sta uh step that comes in the process is mapping your projects to each LPS. Since you have understood what each leadership principle means, you can now assign okay let's say project A meets the requirements of customer obsession or uh deep dive or dive deep leadership principle. So you will assign those leadership principles as tags to your projects. Each project can get maybe two to three leadership principle. uh because obviously one

project has multiple components and it can also be a you know uh customer obsession focused project and it can also meet requirements of dive deep or it could also meet requirements of think big things like that. So assign two to three leadership principles for each project. Um and once you have done that you can next step would be to rank your projects which are like a plus category project, a category project and then a minus or b category project. So that will give you an order or a mental list of what project should come first.

If I am done with these and I am exhausted from the A+ list, I can move to the A list and then I can move to the other list. And all of this process I encourage people to do it by themselves and not dump everything in AI at the first and then ask it to do it because while you are doing all these steps you kind of remember everything all the projects and all the description of it. So when you are answering in the interview it becomes a natural conversation and not like a wrote answer. So you don't tend to forget things. Even if you forget you can modify. So uh these are like my steps and at the end you can use AI to fill in the gaps and then refine the language or structure it or even stress test your whatever you wrote right like you can just be like act as the recruiter or interviewer and then then try to poke holes find out where I can

do more work where I can you know just be more uh just you know just supply more details around my points and such and then You can use that as a practice mechanism. One other thing that keeps coming up especially around Amazon interviews is I know that they really like to you know dig apart any and all numbers you site and you must really have like a strong reason to end up at whatever number you're saying like when you say you increased efficiency by 30%.

You really have to show them how what was it before what was it after exactly where that 30% is coming from. So around specifically the numbers defending piece of all of this. Do you have any you know additional tips around that because that is I think the number one place where the majority of interviewers just like trip. So did you do any extra work around that or is it just a part of the rest of the process that you just described? described? Yeah, that's again a very important point and in order for you to not reach the state where you have to defend first proactive step is uh not have an overstated numbers in your resume or your answers. Do not like it's fine if you kind of exaggerate your project. That's fine. A lot of people do that. We all do that in our resumes. Uh but have that exaggeration uh in a sensible manner. Yeah.

Yeah. Like for someone coming with 3 years of work experience or four years of work experience uh it's not really possible let's say to have given a $100 million profit. Maybe your team work contributed to that but individually it's not possible. So it's very important that while you are conveying your answer your tone should convey the exact work that you did like even if the result was huge the efficiency or the impact was huge the number was huge make sure you uh convey what was your input in that what was your uh contribution to that project if it was a team achievement uh if the achievement sounds not really acceptable. So that is a proactive step.

Second step would be obviously to being thorough with your projects while you're preparing because they do not just test or push back on your numbers. They will also have lot of follow-up questions to explain if if things are not clear or if there is a usage of new technology. They might ask you to explain in detail. So first uh be careful in using the words that you know for sure that you'll be able to explain and uh while you're preparing for the project be thorough in understanding all the background uh all the um all the tools and technologies that you used why something was done why something was not done. uh if you achieved this result, how was this achieved? What was the improvement from the time you started the project? How was your how were your stakeholders stakeholders impacted? What was their reaction? Did

if they took it um act like if they took it positively, did that bring additional projects or additional um advantages to your team? Something like that. So these all could be like follow-up questions. So it's very important to do the background work really well and not just think from a star format answer that if I have like situation, task, action, result ready, I will be good or I will be able to sail through. So yeah, honestly from hearing you talk about this, the biggest realization I'm having is and I don't know if if Yeah, I I don't think Chat Chip had the voice mode when you were preparing for this. Right. Right. Right. So, but I think now that it has that, I just think it would be so clutch to just feed it your notes that you prepared and then just have it, you know, go really hard at you in terms of breaking down whatever it is

that, you know, you're trying to practice for. And I think even if you do that like thrice or four times for each project, I just think every interviewer would benefit so much from doing that because you you're already preparing for the most um FAQ type, you know, back questioning that you might get. Of course, it's not 100%. can never be. But that's still so much more than just going into it blind, you know, just praying praying for the best because obviously that's not the, you know, ideal strategy. So, and then from there, right, so obviously clearly you made it.

Congrats. Great job. And then I'm curious when you first started just what a day in the life was like and I'm curious if you can contrast that now having spent almost two years Actually it's exactly about two years from what you described right I think which you started you said in August yeah so I would love to hear kind of how your day in the life at Amazon has evolved from when you first started to now obviously I understand if there's stuff or projects that you can talk about that's totally fine I'm really just looking in terms of what the work that you're doing maybe the tools that you're using the technologies that you're leveraging that type of detail would be you know really helpful for listeners that are trying to prep for BA2 type roles at Amazon. Yeah. Yeah. Um so yeah it will be I will be completing two years in September. I

joined in September 2024 and yeah two years have been great. I transitioned from business analyst to BIE but um when I started most of uh yeah one a day in my life how it would look like I'm just thinking so I would say 60% of it was uh query writing like working with the data quering the data um or writing transforms ETL transform jobs and making load jobs and all of that. So I'd say 60% of it was that yeah because a lot for a lot of the business requests that we used to get in would need some sort of data to answer those questions and for data we used to query our tables or if we had a request of building our dashboards we would first build the required tables for that from the existing tables. So yeah most of it was writing queries working with the data and then remaining 40% I would divide in doing the visualization part

the dashboarding part uh building the dashboards and um then working with the stakeholders to kind of communicate those insights through uh meetings or reports or the different methodologies that they prefer. Mhm. So that that's what I would say was in the when I had joined. Now fast forward to now obviously we have AI right now and we all are very actively using it. Okay. Okay. So how it has changed is still most of the time is quering the data working with the data but now we have a lot of the tools we have uh integrations to write our queries. We have uh we have like ko that we use uh inside Amazon Amazon Ko. Mhm. So that has that is based on the claude models itself. So we have uh different uh agents available as well custom agents for data analytics work for uh you give a prompt that I'm looking so

and so uh metric which table do you think would be able to help me in that? So there are agents that can query the entire database of Amazon and then suggest you these are the potential tables that might help you. M so right now it's uh I would say AI is involved in every work that we are doing whether it's finding the right table or uh brainstorming about a metric or quering the data and then analyzing the data. uh uh I would say the time that we spent in creating the dashboards and all of that has reduced now a lot because of a lot of the automated uh dashboarding processes and we have different features that that can create visuals u if the data is fed into that. So that part has reduced but right now it's uh yeah it's mostly using different AI tools at different stages right from uh building the pipelines to querying uh the data to

building the tables building the visualizations. Um we work a lot with we spend a lot of time uh working with uh the data to find out the insights and connect the findings from different data points right now instead of just focusing on building dashboards and and creating reports. So that has reduced a lot and a more focus is on how we can find out more anomalies, defects, improve the experience, things like that from the uh data and from the AI tools that we have access to. So I think that's what it has changed. Um yeah.

Yeah, that's very interesting. I'm curious for folks that have joining that have been joining your team more recently. recently. Is there do you think a big change around how they're upskilling for their interviews and such? Like obviously all of the stuff you mentioned is still 100% valid but in addition to that is there now almost an expectation that business analysts or even BIE should be fairly savvy when it comes to just how to use AI or how to prompt with AI or has it not gotten to that point yet?

Officially on paper I don't think it has gotten to that point at least it's not written down. I'm not very actively involved in the hiring process as of now. Yeah. Yeah. So might not as well have a very relevant answer but uh it's I don't think it's very actively engraved on the papers that these are the new requirements for a business analyst but I think the bar has increased definitely while the interviewers are assessing the candidates and while they are assessing their answers. uh usually you know Amazon interviews the loop interviews have a practice of having bar raisers right so they kind of assess if the new candidates's bar is above or equal to the current team's bar if they're if the new candidate would be raising the bar so since the existing team has upscaled and their bar has gone up because of being I see yeah

everyone is being able to um For example, in my team, every one of us have our own personal agents to work upon and also team based agents. We all know, you know, uh how to work with different MCPs and all of that. It's not a secret to us anymore. It's not just for developers anymore. So, all of us can build tools, any tool that we want, any agent that we want or all the services are open to us. So since the team has upskilled I would say uh implicitly the bar for hiring might have gone up but yeah I couldn't I cannot say from the hiring managers or a recruiter's perspective uh but but that's my opinion that it it might have gone up in in how they are assessing the interviewers responses and their answers. Yeah. No, that totally makes sense. And of course, I realize that you you might not be involved with hiring,

but I know you're probably at least talking to people that joined recently. And I feel like just by talking to people, you can just kind of understand a lot of their background. So, yeah, what you mentioned was super helpful and really appreciate you sharing that. Um for this kind of last segment here, what I had planned to ask you was obviously um looking at you know your LinkedIn and while preparing or researching for this episode, I realized that you started off like your roots for your undergrad were actually a really far cry from analytics and data and all of this cool stuff that you're doing right now. So I am curious to explore a little bit around how you like made that transition from a more chemical engineering type background into more analy analytics type work cuz that's that was your first job out after

college even after undergrad. So I know there's a lot of students that reach out to me from India that are you know just doing adjacent tech courses. is still engineering courses but not quite um you know computer science type stuff and they keep trying to ask how do they make that jump. So as somebody that has made that jump what would your advice be to you know students such as that? Yeah, starting in um chemical engineering I wouldn't say was a very conscious choice uh given how you know engineering system works in India. Uh you might be aware of that. So um I was I was getting a great college and I think Alicate is a great institution and I happened to get that uh engineering branch through the counseling process that happens uh for you know after the after you do your 12th and all of that. So based on your

uh scores and ranks that yeah so um and having said that I was not even aware of all the other branches that existed like what I know the names civil engineering mechanical and all of that computer science ECE and all of that but um I didn't really know what any branch entails inside it if you have to pursue that so I went ahead with that um the four years of degree h definitely taught me a lot of the things build my personality grew from being a a teenager to an adult. Um and in those four years besides just learning the chemical engineering subjects I was pretty much active in taking up uh different stuff then as well. I was very active in participating in competitions outside my college like in case competitions or um you know any sort of competitions in uh business competitions or uh hackathons at in those times whatever hackathons

used to be there. So I had a very uh mixed profile at that stage as well and I I had the exposure to uh fields outside chemical engineering. So that that I would say was one advantage which I didn't know I had. Um that I just wasn't aware of the chemical engineering prospects. I was also aware of what could be the possibilities uh outside chemical engineering if I go via this route or that route. Obviously still the scope was limited. I wouldn't say I had all the awareness and I was aware about all the fields but usually I'm the person who likes to try different stuff. So I did that at that time. I had that on my resumeuming like you know case competition participation and different competitions inside college as well. I was pretty active in different clubs and competitions. So had all those all those on my resume

and uh we have placements final year placements in India uh in college engineering colleges and um I happened to clear one of the first role the first to clear one of the first role that I got after my uh undergrad. So I happened to clear that interview for that company that was my second company that I interviewed for my placement. First one was a chemical company and at that stage as well I really wanted to go into the first company that I interviewed it was a chemical company uh but I couldn't clear that for some reason in the last interview stage and the second company that came in was ZS and I happened to clear its case interviews and all of the rounds that it had I I ended up getting into ZS so I wouldn't say it was all planned And it was also kind of destined. But uh maybe the background and taking up extra stuff

in getting involved in extracurricular activities outside my chemical engineering subjects kind of u inherently prepared my brain to handle those case study questions or those type of interview questions which is very different from chemical. Yeah. uh so I would say that's how I prepared and to the students who are currently right now uh in undergrad and they want to explore options other than engineering I would say this is the best time they could be in because of the resources everything is available online for free of cost and in high quality you know like there are so many u videos on YouTube and resources online so have those experiences through internships through projects and through different ways is on your resume or of whatever field you want to try. Just try a few things of that field. How does it look

like of whether you like it or not? So that will give you a taste of uh different fields on what the work is like if I go into this field or that field and have those on your resumes. So that will help you some way or the other as you progress in your career or as you are heading towards your first job. I would say yeah and actually even related to that something I've been telling students that reach out to me around this is that this is probably the first time in history where there is no longer a need to take and finish a course to learn something cuz all you need to do is just honestly you can even go really far without watching a single YouTube video either because all you have to do and now for the first time ever you have the greatest coach in technology history tailor made for specifically the way you

like to learn and you as in is each individual and so obviously a lot of people leverage that but a lot of people haven't quite caught on so I like to make this point every chance I get that the best way to learn something today you know like 2026 and after is to start with you know your AI of choice you know just share what you know what you don't and then just have it quiz back and forth, generate case studies, generate like course material that you can read through exercises, and then you know before you know it, you'll be at least at decent enough 101 type level at pretty much anything your heart desires.

Final question before I let you go. There's a lot of talk around folks that say either that the US is no longer what it used to be in terms of international students or like especially students from India to come here for their masters and you know the life beyond that and there's also a separate group sometimes it can be a subgroup of people that say that if you don't have at least two to three years of workex in India don't even consider consider doing a masters in the US. So obviously those are two hierarchies. I'm curious where you personally stand on these these and obviously I know this is subjective right you're not claiming to be this is what you must do so I will happily preface that before you do but just from your POV are either of those true and if not like I guess yeah where do you stand in all

of this in terms of guiding people because this is a question that I'm sure you probably get and I also get a decent amount. Yeah, that is true. A lot of people on LinkedIn or in general people who want to pursue masters here reach out and ask if it's the right time, if we should come here and all of that. And my answer would be based on the experiences I have had and the people I have interacted with and obviously I will have very limited scope. I I I just spent like three will be spending third three years in this country. So very limited scope. um to your first point on um whether US being relevant for international students or in terms of opportunities and all I do think it's it's getting very difficult like it's a tough time like with each passing months we are getting some new news and restrictions and all of that so

it's getting difficult definitely uh having said that I still do not feel that opportunities are not there uh the market is definitely brutal and a lot of people might come up to me uh when I say that that of there are opportunities are still there because market is brutal and there are a lot of people facing uh issues in job search and all of that. uh but somehow I still am very optimistic that uh people are able to find opportunities and people who are cons consistently behind it and they are able to find one opportunity after the other through persistent following uh of people by amplifying their skills by reaching out to people by trying different uh methods. So I think if you are optimistic and if you are flexible enough to mold yourself with this new technology, widen your scope, uh try different new things, uh go outside your

comfort zone, talk to people and all of that, you will be able to find opportunities, but it's a hard nut. It's getting a hard nut to crack. I would definitely say that it's definitely not easy. It would require more and more effort. uh than it required like maybe few years back. Mhm. Mhm. Um on your second point, I kind of agree that you at this stage you need to come with few years of experience here at least two to three is a sweet spot.

three to four maybe u sweet spot because uh and again limited to the people I have talked to but I have been interacting with a few undergrads recently who came from India and other countries and they have been finding it really difficult to find fresher uh roles. uh they have been looking at looking in the market for a while and they have been finding it very difficult because a lot of the uh fresher roles also says that they need two years of work experience or one year of work experience which is unfair for the bachelor's student or undergrad like how will they have one year of full-time experience besides the internship and companies do not consider the internships as fulltime. Yeah. So I think yeah maybe for uh that part coming with few years of work experience might help uh but 3 to four or 2 to three would be

a sweet spot and I also wouldn't recommend recommend going into a very large experience bucket like 10 plus years 20 plus years unless you are uh getting a really worth role that justifies your uh years of experience. friends here. Mhm. Mhm. Yeah, that's actually really interesting because I've never once considered what it must be like for somebody with 10ish even 10ish years to try and consider moving here. That's very interesting.

Yeah, I I'll have to think about that. I've never once considered that. So, yeah, thanks for I guess planting that seed. um one piece of advice that you would share with business analyst enthusiasts or folks that are trying to crack business analyst roles. One piece of advice if I have to sum it all would be focus on your communication skills. When I say communication skills, I do not mean the communication me and you are having or the communication we have in general. And it might apply to a lot of roles, not just business analyst, even better. But communication means the confidence to speak up in rooms where you are not sure of your um response. the confidence to uh share your ideas or share your questions in a room or uh in in a room full of leaders or in a meeting full of uh leaders where you are afraid that you

might be judged or you might your idea might not be worthy enough. Have instill a a thought in your mind that if you have been invited to a room uh full of people irrespective of their positions, you are worthy enough to sit on that table and share your opinion. So do not doubt yourself. I think people starting out especially in the early careers mid-career also everyone has the imposter syndrome but shut your brain down there and let it speak let your ideas speak. Um also communication about your work. So I have realized now that just doing the work is not important.

Talking about your work is also very very important and many are times more important than doing the work. So talk about the work you have done. Uh do not brag about it. Do not exaggerate. There's a fine line between that but uh talk about it to so that people know what you're doing and what your contribution has been because unless you talk about it people are not going to know. Everyone is busy in their own work and lives. So um I would say focus on building these communication skills and most of these would come when you accept being uncomfortable in the space because most of them asks you to be uncomfortable unless you are a very extrovert person and you like to do such things. Mhm. So and and same applies to uh communication that comes from translating your uh data points and all of that into insights because unless you

translate that into business insights, they are not useful. you know the business or the uh your stakeholders are not going to do anything with your uh advanced formulas or logics and all of that unless you tell them how is it going to impact the business or what do they need to do uh to drive the change or make an impact or launch a product or whatever. So all of these fall under the bucket of communication. So I would say uh give importance to that as you grow in your career and keep learning uh different hats of uh communication.

Yeah. No, that's awesome. And I think not only what you said is super duper critical and often underlooked. So, I really appreciate you bringing that up. But I think what I'm walking away from our amazing conversation here is just this idea that keeps coming back is it's so interesting to me that your entire life path almost went the direction that it went in just because you were willing to experiment in college just with stuff that you know just was drawing you for some reason. Like again to your point, you went out of your comfort zone to do these case studies, hackathons, whatever it was. stuff that you weren't necessarily supposed to do. You weren't expected to do them and then it's so interesting how that put you on a path that has since brought you here. So, I don't know. That's just something I

wanted to spotlight and it's part of why I enjoy doing this so much. Like why I enjoy these conversations so much because they're they're just so illuminative. I don't know if that's the right word, but about, you know, just life and just what can happen if you if you're just willing to, you know, do a little bit extra, a little bit um putting yourself off, you know, out there. So, and I know I've obviously taken up way too much of Yeah, exactly. Showing up, right? Especially when you're not expected to. And there's just something about that that's really really powerful. So, this has been so awesome, Sami. Thank you so so much for taking the time and for bearing with all of my like 39 reschedulings. So I'm glad we finally able to make it work and hopefully you enjoy it just as much as I did. did. Yeah, of course. I I just wanted to plug

in one thing since you were saying about how things worked while trying to experiment different things. So um you know as Steve Jobs mentioned that you can only connect the dots looking forward and um so I was I was reflecting that when you said that about my path and that's what has been my philosophy kind of uh as I go ahead as well of trying different things. Some things work something doesn't it just tells me this is not for me this is for me and I choose and then one thing leads to another. So keep your uh uh path open in terms of accepting opportunities and willing to just step a bit outside of your comfort zone and experiment.

So yeah, that's been my experience so far and it has been uh fruitful to me. So I would say that to people as well that it's worth being experimentative. Yeah. Yeah. Awesome. Well, thank you. Thank you. Thank you so much. Yeah, thank you so much Naman. Thank you for reaching out first of all and I'm glad we could do this. I hope I hope it was worth for your viewers to uh listen and watch and uh we did a good job or yeah we will I tried to well as far as I'm concerned 100% and as for the viewers we will just have them let us know in comments and by reaching out to us on LinkedIn and such.

So we'll find out in due course of time. I'm not too worried.