Joining. I'll just start a brief introduction about myself. So my name is Arbani Paul, and I work at Amazon as a technical program manager.And thank you for to the Omen Intech for giving me this opportunity to, you know, share my experience. So I would say that this experience is completely about myself. I was in consulting for a couple of years. And then, like, an year and a half ago, I made a move. I joined Amazon as a technical program manager. So I just wanted to share how it went, my journey. Like, what are the steps that I have taken and what are the prep strategy that I have taken to move to from Big four Consulting to a Fang company. So anyone in this journey or, like, who is willing to, you know, change their career and move from consulting to tech or any product, not necessarily it's Fang.

So probably this presentation will help you or encourage you or maybe helpful, like, to how to take the next steps. So the journey is about not only a carrier switch. You know? It's just about the complete mind shift change as well, mind shift mind shift transformation. So for years, when I said I worked in consulting, where success is being measured very differently in consulting. So success always means, like, the recommendations, strategy decks, and then client presentations. And that's the very first step in how consulting actually works. We go as an adviser, help clients understanding, you know, how the solutions they can build, and then they work on by themselves. So we just give them the proposal. But in FANG, it works very differently, where impact is measured very differently in terms of, like, they look into the system, the scalability, how the customer experience is, and how the execution will takes place.

And my presentation is really about three things that I'll talk about, like what consulting taught me. That means how it helped me to build my career and how I made the transition. There are few things I need to change my mind shift when I said, meaning there are a few things that I had to unlearn as well and adapt to the new learnings. The third is, like, how I successfully made the transition into that tech. And then I hope anybody who is considering a move into product tech or any fang style will be helpful with this presentation. Now in my next slide, I'll talk about the foundation. That is the strategy at scale.

So what my consulting background actually taught me is, you know, I learned how to operate the business or operations in a large scale. A lot of my work was involved into, like, digital transformation, process optimization, executive stakeholder management, and data driven recommendations. One of the biggest advantage that consulting gave me was, you know, I learned how to break down ambiguity, how to effectively communicate with the advisers or, like, my clients or the stakeholders, and very difficult or complex problems that how can I simply explain it to a layman in a very layman's language that so that they can understand?

So I also learned how to work under pressure and operate in a very, you know, fast paced environments. However, in consulting, often focus on recommendations. But in FANG, recommendation just a starting point. Here, execution is everything. That was a major mind share mindset shift that happened in my career when I decided to make this transition. And then in my next slide, I would talk about the the moment. This slide actually captures the exact moment, you know, the where I realized I want to make something different. So there are a couple of things. Like, when I remember the first part of my career, like, when I actually went for to help or consult a client, like, how can they expand their business or, you know, how can they save their inventory savings.

That's an example of one of my project. I gave them all the ideas how they can actually truly get the success, what are the steps they will take, how they should execute the project. But at the end, the project presentation went really well, and everyone was happy about it. And they also accepted the proposal that we have given. Since it was very client phased, I actually what I realized is I never got to see whether the proposal that I have given, they accepted how it was implemented or how the customers was being, you know, succeeded or the the experience of the customers, I would say. And what are the technical challenges that I have proposed, if there were any technical challenges, I never got to heard any of those. And that's what bothered me, and I just wanted to I just realized that I just don't wanna advise anymore. I also want, you know, some kind of ownership.

Stay very close to the execution and see how it's impacting the customers. Or what are the, actually, benefits that I'm bringing? How much I could save, like, you know, in terms of when you talk about, you know, I'm trying to save the customers to save some some million dollars. How that actually impacted? So in FANG and also the motivation in FANG is, like, I was able like, when I was do doing some kind of research, like, few of the target companies I had, Like, everyone has a ding to work in Fang once. So similarly, it was mine as well. So mostly, what I what got me attracted in Fang was, like, end to end ownership. I could actually stab billion user impact or the how the data actually talks.

So I'll talk about each one of them when I'm talking about three major, you know, the things three major actually, my motivation that made me to move to FANG. The first one is end to end ownership. So in consulting, the projects are always time bound. But in FANG, the FANG own their own products and systems. So which means you build a solution, and we measure the outcomes. And also, like, the iterations happens continuously based on the learning how the customer feedbacks are coming, which I'm getting to see in real time. And, directly, I'm also the same time learning. So that how can I iterate and make those make those iterations even more effective? So the ownership mindset is very valuable to me, which I wanted to get in a FANG. And then the next one is bill billion user impact.

So in Fang, what I have observed is even a small improvement, one of the project that I'll talk about, like, onboarding sellers. Like, since it's I work at Amazon retail, I'm trying to onboarding sellers effectively. So, like, how I'm doing that? How what are the impacts that I'm making and how once they're onboarding, how their journey is being, whether they are able to make a smooth transition to the Amazon portal. And once they how their business is performing, what are the amount of million dollars profit they are being bringing to the bringing to the for Amazon. So that tiny improvements in or, like, scalability in in the website that I was actually fascinated by the numbers of the datas that, you know, I I'm able to see right now the impact. And then as I said, the data.

Data is always one of the thing that makes me excited in terms of, like, I'm seeing the value that I'm adding to the project. So the next is real time data and feedback loops. So in consulting, what happens is feedback loops are always it takes some months because and that too, I'm not sure always I'll have the feedback because sometimes it happens once I left the project. That's it. I'm done. I don't know what's happening next. But there are some other colleagues who is going back and working in the same project, then I get to hear something. Okay. This much this project is helping and, you know, made this much million dollars. But that's very rare. Like, we don't actually get to see.

So feedbacks are always not necessarily I get to see immediately. Whereas in in FANG, it's very immediate. Once we launch one product, and I immediately get to see. Like, we monitor metrics immediately. And as it comes through the data, we keep iterating all the time. So that data driven culture is very exciting to me. I realized that FAANG is just not a job change for me. It was also a shift from my advising business directly that helps shaping customer as well. In my next slide, I will talk about few of the things that, you know, I had to unlearn and, like, you know, not unlearn other I'll talk about the differences or the challenges that I've I have faced. In FAANG, what happens sorry. In consulting, what happens, it's always slide first. What it means is, like, we learn how to being the very polished narratives, how to make a very good presentation.

The client will get impressed and accept our project, and they will take the proposal. But in FANG, they always value speed, experiment, and shipping. So that's what I meant by first slide versus action first. And the second one is analysis paralysis. What it means is consulting heavily focuses on extensive research and before we go back to go to client proposing them some solutions. And it takes sometimes because we go in iterations in doing some research and then giving them the feedback or, like, any solutions that we are providing so that they can get the best outcome of that. But in tech, in what I realized, it's something different where waiting is you know, it's not too long. So I had learned even though we don't have all the information at once or readily available, I learned to make decisions with imperfect information or partial data or, like, fast moving information.

Like, how can I get information quicker? Like, not like, even though I have the half information, how can I start building the solutions, or how can I help it? This was actually initially a little uncomfortable for me because I'm always used to get the perfect solution. But I have realized this mindset needs to be a little bit I need to change so that I can get a faster result because there is an option to iterate, and I'm gonna work on that. So it's very that's a little bit of challenges initially I had, and that was the mindset I also had to change that not always thinking of perfection. Just start doing what I have, and then eventually, I can iterate and get those faster or, like, get get those modified. And my next one is unlearning perfection. What I'm trying to mean is this lesson deserves its own slide actually by its own because it fundamentally changed how I used to operate before and how I operate right now.

So early in my fan carrier, I spent too much of time, you know, trying to make things perfect, as I said before launch. I then realized that I need to do something different. My approach needs to be a little bit different, and that's and that definitely, that's not a failure, and I have opportune to make the feature enhancement and go from there. The goal is not actually to build a perfect vision in version immediately, but the goal is to learn first, test assumptions, improve as we go through. That was a mind mindset shift that was required. And now I'll talk about the prep strategy that I have taken probably that might help you if you are just looking to make the move.

So when I decided I need to make a move, so there are I first thought about how can I split those? So I wanted to give myself three months of time to just prepare so that I can once I get the interview call or I am trying to apply, I know what I'm looking for or I want to be successful, basically, once I start interviewing. Because interview calls are another thing that's not easy to get. You need a lot of referrals or sometimes apply online, but you definitely will need to be prepared on what coming next so that you can correct the interview. As I'm from consulting background and moving to tech, so I definitely understood that I need to enhance few of the skill sets because in consulting, we do business and operations mostly. So I also, the first step was that I need to be technically a little more advanced.

Like, I need to learn few more technical things, or I need to see how product actually works. More of product sense, I'd say, and how I can improve that and implement it or, like, I can track my interview. Few of the first month I gave myself, you know, to enhance my skill, I started focusing on product thinking. And then definitely as a for a TPM, if we were applying for, we also need to have system designs, concepts very clear. And then also, like, engineering workflows, how it works, and also the technical fundamentals, as I said earlier. We need to be technically little efficient. Not that I'm trying to be an engineer here, but technically, we should be able to understand how the system functions or how the system works.

So that that helps actually to drive the conversation with the engineers or any technical person you are talking to. Because in product, what happens is there are a lot of stakeholders involved product, engineers, operations, so how I can communicate those. Like, once somebody's talking about technical stuff, I should be able to understand that even though I'm a technical program manager. So that was the few skill set that I was I would say, like, anybody who is coming from consulting, business consulting back background, one of the thing is to definitely start beginning with try to enhance your SQL skills. And also product sense, how you think about a product or system design you need to prepare. And the second month, what I did is once I felt like I'm a little ready, you know, prep myself, I started networking.

I started connecting with people in LinkedIn who are actually working on like, from my target companies that I had, I started reaching out to people who are actually working in those companies. There will be times where people I mean, not everybody will respond, but what whoever is ready to respond. There are really some nice people who will be willing to extend their help in terms of how what the expectation is, how can you crack the interviews. And, also, I had met few of the people who for the coffee chat or something or, like, got into a call to understand more. So what that helped me is to understand in a tech how what the real expectations and what are the hiring patterns and also, like, what skills actually matters, how I should improve myself so that I can lend the offer. So once I had that developed in my month two, in my month three, what I have done, I started mock interviews and more practices.

So when I say that, that means I started practicing practicing extensively the examples in a star format. And then also one of the thing that must you know, behavior interviews are very common in any of the FAANG interviews or any product interviews. So behavioral interviews. And then I also worked on project management scenarios and then metrics given answers. So any examples that I'm give I'm talking about, like, how I'm deriving, meaning what are the impact that's being made. So and then in my fourth month, I started applying and lending to the offer. And the next slide, I'll talk about one of the very important topic is even if you get interview call, cracking the loop interviews where it happens, like, five rounds, six rounds at once, how you can improve that?

What are the few things that you can consider? So when you start telling your stories or you build up your stories, first thing you should remember always it needs to be a STAR method. And because they're just not in STAR method and also in definitely in the metrics, like, what like, for example, I would say, like, this much million dollars I have like, my project or my work has the data in terms of, like, $1,000,000 I could improve. So you always need to give them the numbers. That's just because they don't evaluate you how you communicate. It also because how you are like, what was your ownership? They love hearing your decision making process. Your how did you handle ambiguity? Or how the it was customer obsessed and the technical implication or technical ideas that you are given.

And also how definitely, any company you are looking for or interviewing for, make sure you look into their principles and then try to adjust your answers accordingly so that it fits into their leadership principles. Like, when I talk about Amazon has 16 leadership principles, so you can get questions from any of the principles, leadership principles. So make sure you prepare two or three examples from each principles. And I feel like since Amazon has more number of leadership principles, that is 16. So that actually helps will be helpful to for you to actually crack any other interviews because what my experience is, like, leadership principles number of leadership principles are actually lesser in other companies. So I would say focus on even if you have interviews for Amazon or not, but try to focus on their leadership. That will cover everything. And that will also cover your behavioral interviews. And then next, you would, like, also need to focus on system design thinking.

So, basically, not as as an engineer level, but you also need to understand how the workflow happens and how the data flows from starting to end. So that's another thing. And also develop your product sense, like, an just research on one of the few products that the company is working on, try to develop then. And then the last is the execution, definitely. Give some examples on, you know, how the program is focused or how the execution you drove and then that was successful. And the main difference, I would say, consulting versus, you know, FANG is, like, the in in consulting, ideas matters. You bring in ideas, the solutions you are gonna provide. The strategy that you build to get into the solutions, like how clients the you give the strategy to the client to help them execute, and then the executive communication also matters. But in Fang, it's little different. Like, execution speeds matters, but very effectively. And then metrics matters.

Operational scalability matters, and then the customer impact that is actually visible to you. Throughout my journey, one thing that I have learned is, you know, I learned how to be more empathetic to the engineers because consulting sometimes encourages idealized solutions and tech taught me about scalability, reliability, trade offs, and customer experience. And I also learned that data is very important in products, so we always talk through data. So more than opinion, when you give your opinion, you make sure that you have the datas to back up with. Do some research how this project is gonna work. You are giving some ideas to enhance a feature or anything. Make sure you have the data available for that. So the my final statement would be, like, you know, if you're really trying to make a move here, the you all of us had some kind of skills already.

It's just that we need to format it the way we want it to or, like, how we should be doing it. So people who are in consulting and making to make a transition, we already have the communications in place. Stakeholder management, know. Structural thinking and problem solving. We just need to combine this through our ownership mindset, technical capability a little bit, and speed and execution. And that's all. I hope whoever is looking for to make a move, my presentation is helpful, and that will actually inspire them. And anybody who has any questions, I'm open to take any questions if you have any.