This edition of #WhatIndustryWants highlighted the potential careers for graduates and young professionals in the booming space of the tech and analytics industry. Ashish Sam, Sr. Partner, People & Operations, TheMathCompany, the distinguished speaker for the session, discussed the career opportunities aspirants could explore in the tech and analytics space and how aspirants can train and build such new capabilities, and more. Watch!
In his 18 years of experience, Ashish Sam has spanned the entire gamut of Human Resources functions – Talent Acquisition, Employee Engagement, Performance Management, etc. Before joining TheMathCompany, he worked with leading corporations such as Tavant Technologies, Mu Sigma, and Bridgei2i. As a transformational leader, Ashish has played a pivotal role in building, nurturing, and engaging talent across these organizations. On an academic front, he holds an MBA in Human Resources. Know more Know more
TalentSprint, a National Stock Exchange (NSE) Group Company, brings transformational high-end and deep-tech learning programs to emerging and experienced professionals in partnership with top academic institutions and global corporations. Its patent-pending, AI-powered, digital learning platform enables a perfect blend of high-end academics and industry-leading practitioner experience. Its programs have consistently seen a high engagement rate and customer delight. For more information, visit talentsprint.com
So good afternoon everyone and thank you for joining our what industry one series episode four powered by talentsprint or National Stock Exchange group of company. And as our industry speaker today we are joined by Mr. Ashish Sam, senior partner people are people and operations at the map company. And Quick, quick introduction about our Sheesh. In his 18 years of experience. She has walked all walks in the HR HR function, talent acquisition, operations, resource management, employee engagement of etc. And she has worked with leading corporations such as talent technologies, music Ma and bridge eye to eye in the past and brings a wealth of knowledge and expertise to the table. He has played a pivotal role in building nurturing and engaging talent across these organizations. Course believes in being hands on as it keeps him closer to reality is a thought leader, more importantly, a transformational leader who strives to build future ready workplaces that always put the people first. She is a fitness freak and loves to practice mixed martial arts and CrossFit to burn off the extra calories from his sweet tooth indulgence. Awesome. Ashish, thank you for taking time out on a Saturday afternoon and joining us to share your wisdom and insights.
Thanks, because Thanks for the introduction. Hi, everyone. Good afternoon. I see a bunch of questions coming in. So they're very interesting. You know, I look forward to answering some of them. But yeah, go ahead. Because what do you have in?
Sure. So the format of the webinar is a it's a candid chat around some curated questions. I think some of the questions being asked here are kind of picked it up somewhere or the other here. However, we have also allotted last 15 to 20 minutes of the session for questions for or maybe half an hour. If If our questions are covered up in half an hour, maybe half an hour for four quick questions from the audience's. And I will make a note of your questions and during the last allotted time. So Ashish, to quickly begin. How should one identify the math company as a company, a product company? Or a technology company?
Sure. Okay. Great, great question. So thanks, because I'll quickly some briefs about my background, also a little bit. Some people asked me, What is my package in the 18 years that I've been working? Frankly, that's not what I'm after, I think after more after experience, and I think, in hopefully, I will cover some of the questions that hopefully, because as I'll cover some of them, I'm based out of Bangalore guys, and I hope all of you guys are safe. I think one thing that I'm just noticing in the chat is everybody's addressing sir. That's the first rule that I have learned in my 15 years, at least that I've been working is to address people by their first name. So please feel free to call me Ashish. You know, Don't address me as Sir, I'm not titled in any form. I am not unique. I'm as simple as you just may be by yours, but it doesn't give me the authority be titled as a sir. So at matco, wherever I've worked, we are all called by our first names, right. Okay. Now jumping into the question, I've been with Matt company for the last three and a half years. And of course, like, because mentioned, I've, I have a decade and a half plus years of experience. My career mostly has been in analytics. I've spent, you know, about easily about 1012 years in other organizations in the analytic space. And I've done various roles as well. madcow, from the time that I've joined, and I'm not, you know, trying to give more details in but I joined at 50 people strengthen today we have 700 plus. Right? So that's significant growth for us now. How should you identify the map company, and we've transformed as an organization, we're just entering into our fifth year anniversary for you know, a company that is completing five years having a strength of about 700 people. It is phenomenal growth. And we've been rated, you know, by the light in both 2019 and 2020, as one of the fastest growing AI ml organizations out there, right. So, if you look at it, there is data science, data engineering, is it a analytics company? Is it a product organization, technology company, I think we're a good package deal, right. So one, we are an organization that's focused on problem solving. So, irrespective of domain technology, we are here to solve problems. So you will not find that we are you know, working on a particular vertical beat like retail CPG or technology. We don't focus that way, we're here to solve problems or our customers problems that are unique, high value problem solving, things that will transform their business completely, right. And we use AI ml to power some of these solutions for our customers today. So you could say, we know how we like to call ourselves is a full stack data center. And, you know, we do data science, data engineering, product engineering all put together. One is what how we package our solutions for our customers. So in math company, everybody is, you know, does data science data engineering product engineer, and that's how we want to transform ourselves out there for our customers in the long run. Right? Because that doesn't answer your question.
Does that does? In fact, my second question was also around around the same. So what does technology mean, at the math company? And I mean, is it possible for you to talk about some of the exciting technology projects may be going at? I mean, what's going on at math company? Not? Not at a very, I'm sure you're not like to discuss it at length, but at a superficial level, do you think you'd be able to talk about some of the exciting technology projects? At the math company?
Yeah, absolutely. So like I said, right, I'll maybe try and talk about one or two examples. You know, if you go through our website, you will find enough and more case studies for you to go through, right. So I'll talk about what is mostly like a CPG organization, you know, a leading confectionery and food manufacturing organization. So, in their production process, there is a research team that keeps constantly looking at, you know, articles or research papers that used to get generally published on what are the type of products that needs to be used? And, you know, what are the approvals that needs to be gone through, and this is like a research papers that people like a long queue of people have to sit and do and has to be put into production, live at any point in time, and it's a painstaking process. Imagine going through research papers, one after the other identifying key materials, and maybe you read a document, it's not even relevant, right. So we were, you know, we started off this task for this specific organization, and we used, you know, data science, data engineering, and, you know, put it together using NLP deep learning to be able to build a product, which will automatically, you know, identify such articles from the web, process it and call out the specific, you know, links that need to be read or the portions that needs to be right, and hence, decision making processes faster. And it was automated completely. So imagine, like a bunch of people who are going through these physically at one point in time, and all of a sudden got automated, and, you know, amount of time that was saved, was easy. And we could change products as a product features, what needed to be researched on and it was scalable, to multiple products that was possible across the, you know, their array of products that they had, right, and, you know, it was done in a period of about three months. And it was a big experiment, our accuracy rates, if you look at it, any AI ml model has to go through, you know, a lot of training, right, and our accuracy was at close to 97%, which is a big achievement, for example, right? That's the amount of impact that we were able to create for one of our customers, our customer, let's say like a shoe manufacturing organization, right. So they these guys, man, and this, this is also there on our website, as well, they kind of, you know, create specific branded products during a particular season. And there, it's available only during that season, and it's off the shelf, there's a very unique product right. So, they wanted to experiment and figure out which product and which market will work out versus not work, right. And they had to do this, you know, trial and error trial. So we build a product for them specifically and you know, by putting in all the relevant variables, you know, it could easily do these you know, multiple iterations to say what will work in a particular location. And in real time impact was created for that customer, right. And they were able to launch products easier, faster, better, time will save energy will save and it was all system driven. And this product is in their platform are in their environment, epically
fascinating Ashish Berman, it's so fascinating listening to I went to how you guys are solving real time problems. I think I think we can just talk about it. Day in and day out. And it will be fascinating, as sorry, as she was saying something I don't know. I'm just saying
there are things that we see in our day to day lives which we build over and not know like, for example, the chat bots that gets pinned there's a lot of work that goes behind it. And it can actually easily run you through at least five, six questions before you figure out, you know, your answers. You don't need to talk to anybody. Right? So, you know, I just feel that technology has to be leveraged so much automation has to happen. And the big question comes, okay, if automation happens, what will happen to my job? That's a big question that everybody asked, but I feel that, you know, you have to move on and do other things, there are so many problems to be solved to this world. And you cannot get stuck saying this is the only thing that I will do. Right. And, you know, let's say I want to see some of the questions that come up from folks and maybe address some of those interesting things and perspectives that I have in terms of how you need to build capability, what is your what should be your perspective as
well. So upskilling is the key. I mean, your underlining statement was upskilling is the key. I mean, you can see where where you are coming to the next question, Ashish, what profiles are or maybe what skill sets do the math company look out for or hire for? And what does an ideal candidate look like? to you and to the mat company? team?
Yeah, good question. See, if you look at it at math company, we would not have been able to scale in the last five years from zero to 700 people that we are today, both India, US, Europe, all these locations, right? talent is, is a it's like a war out there, like everybody is going after the talent, right. And everybody wants to get into the right place. They're asking all the important questions, all of them. At my company, I think, one what we look for is the ability for people to think through a particular problem I The answer is not what's important, but the thought process is what supported the no give up attitude, right? I will keep trying, I will keep learning. You know, I will go and explore whatever is required impossible for me to be able to develop as an individual, right, and I think, and then of course, communication is relevant. skills can be taught, like I can teach you, you know how to do modeling, I can teach you how to build a BI dashboard. All those are learnable traits. But the attitude is far supersedes anything and everything else, right. So if you look at it, most of the organization, most of the people that we hire, I think these are basic criterias that we look hunger, to learn and do more is going to be, you know, far more important, right. And we hire diverse candidates. So it's not like I go to engineering colleges, because in India, of course, the vast talent available, and I'm sure 80 to 90% of the group that is here today. You know, I see about 350 people are mostly going to be engineers, but we also look for people who have done maths, stats, economics, operations, research. All these are, you know, good, good skills to have. And when talentsprint organizations like that sprint are training candidates, and that becomes an easy supply for us to be able to go and talk to these people and hire them. Right, because it's ready to train talent that is available as well, right? Yeah. I think just to structure thinking problem solving, go getter attitude, I think those are things that we look for in an individual, of course, because depending on the range of experience, knowledge of technologies and tools are important, like Python SQL, all those is relevant, but in general at the baseline, it needs to be whatever I spoke already.
Great, thank you for answering to answering to that question. Ashish. Ashish, now this just little off of the the line which we are discussing, I see the logo behind. I mean, the the map company logo, the three dots? Yeah. What is it? resembling too?
Good. I can I open up this and let people die? Right? And can people guess what the three dots mean? I'm open up it for somebody who wrote it. Okay, Rahul, you got it. Right. It's therefore. So we say therefore, we are the bath company. Right? So that's our, you know, that's the logo that what it means. A lot of people said, is it three co founders? No, no, that's not what it is. It is therefore we are the math company. A lot of people forgot. Like, when I did problem solving, or when I did, yeah, now I remember. Yeah. Therefore is what do you do a really
good one there. Yeah, they should good one there. Okay. Great. So coming to the next question. So how does the math company so of course while interviewing you identify the right talent and you identify and the skill sets and so I
think we've got some taking some time to join us. Okay, guys, I don't have any spare because because it's not showed any questions to me. I'm not sure what those questions are, what I can do is till he's back, I can share something with you
let's clean. Hey, folks were able to see. So guys quickly I am just introducing the math company spoke about this before but you know we are we based out of Chicago Dublin and Bangalore these are we have locations across the globe, we work with fortune 500 companies out of which we currently we are working with about 50 plus of them today. Like I said Our strength is 700 plus people data engineers, data scientist, consultants, subject matter experts all of them. We've been, like I said fastest growing AI ml, you know, certified by Deloitte both in 2019 and 2020. We've been certified by a lot of other platforms as well. We've talked in data scientist and 40 under 40 Awards, like we have two winners in math company as well. Right. So that's quick background about us. Because Are you back?
Yes. I'm so sorry. There was like a power fluctuation. I'm so sorry about that. I'm so sorry.
No worries. No worries. Yeah. So I will just stop sharing. Now, if you want to take this. I'm okay. No, no, no, I was just trying to fill in. That's it. Right. Is my screen visible? No. Is it?
It is It's okay. I mean, if you want to keep it.
Yeah, no, I understand. I think we are all working from home.
But it's it's a challenge again.
Yeah, no, I understand.
So Ashish, my question was for our trainee is that talentsprint. And for all our listeners today who aspire or who are data enthusiasts, who aspire to be data scientists, data analysts? What are some of the key areas they should focus on?
Sure. Okay. I think I saw a lot of questions saying I'm a fresher, I've done engineering mechanical. Yeah. I want to try and address that as much as possible. So guys, in in math company, at least, you're, you're behind engineering grants. And we don't go to a particular department saying hire only computer science grads, or electrical engineers, or EC folks, we are open to all branches, right? I remember when I started initially, hiring for analytics, people applied for an index because they they said, I don't want to do a coding job, right. But unfortunate, I'm sorry, I have bad news, you coding is going to be part of everybody's face, you know, if you want to you if you want to survive in this industry, or in this world, coding is going to be by default, something that you have to do, right. And when I say coding, I think coding has become so much more easier. These days, right? I believe what I understand is odd in Python are far more simpler to code in comparison to what it used to be, you know, coding in Java and dotnet. Right. So So, you know, you are ability to code is going to be your, you know, programming skills is mandated, I don't think you can ever get away from that, right. And, you know, people say, you know, you cannot be biasing, I will do only data science, or only data engineering, the world is evolving, where the, the line between a data science and a data engineers becoming thinner and thinner, right? Your ability to, you know, do anything that the customer needs is going to be the world, right? So, you know, be data science, data engineering, product engineering, a full stack data scientist, is what you need to aspire to be. Right. So, you know, I would say things like SQL, R and Python are today, you know, some of the hot skills that are there in the market, but I believe me in the next six months, this could completely change, right. So don't be surprised, right? Things like big data, you know, knowing cloud architecture, infrastructure is going to be critical in the next coming few months and years. Right. That's where the world is moving. But I think the attitude that you need to have is that I am willing to learn I will try something new. Anything that comes out there in the industry, I will keep myself up skilled and not put a bar saying okay, no, I will not do this versus I will not do that. Right. I think that's the that's the thought process because because you need to always be honorable, always willing to learn even at whatever age you are, right? It doesn't matter your years of experience because if you don't learn, if you don't keep evolving and changing you it's as good as retirement.
Right, Ashish? So I went from the last two questions. My my key takeaway, at least for me, my the key takeaway was attitude. So I sense attitude is the key area or key skill set, which you look at while evaluating prospective candidates or while evaluating prospective. prospective applicants, am I right?
Yes, yes. So even when I talk to a lot of candidates beat campus, or lotteries, I think one of the questions that I keep asking is, what have you done? You know, differently, right? I've done my regular stream of work, and you know, I've got things done, but what have you done outside? Right? This is just mainstream just work. And if you if you are in an organization, how do you ensure your your life is just not about, you know, delivering projects, but a lot more. And I think at my company, we try and give opportunities to people to build themselves holistically, right. You want to be part of training, you want to coach and mentor people, opportunities that you want to lead initiatives, opportunities that you want to be part of CSR functions, there is a chart. So in math company, there's there's so much more like, you know, I and I strongly believe in, you know, not strange jacketing yourself doing only one word, but evolving as an individual requires you to be able to do different things. And it could be even within your own team. Right. And, you know, like, do I want to drive initiatives in my own? Right, and it could be a learning function, or it could be a fun function, it doesn't matter. But collaboration becomes so much more easy.
Right? Agree. Absolutely agree. So while we're talking about the mentoring and the coach, I'm familiar with it. However, for the benefit of of our audience and our listeners today. How does the math company invest in people development? Ashish? And I know for sure, a lot of effort goes there. But but from from you, and how does the math company invest in people development?
Yeah, I think, great question. I think every organization in this industry has to invest in people's learning and growth, because one of the key skills is to always upskill yourself, but how do you keep doing it, if you're doing work on your own, you know, you're not, your ability to learn becomes even difficult, right? So we have a function that is in our organization called coach. And this team is with a fork, and it is not an HR function. That's which is very, very different. It doesn't come under the HR umbrella, it's driven by business, and focuses on upskilling. Everybody in the organization, and there are different ways and means of doing it. Right. So we have folks who join us from campus, they go through like, you know, anywhere between four to six months of training, and they go through the whole full stack, right? Starting from, you know, how do you define a problem? How do you solve problem? How do you structure a problem into basics of programming, and, you know, all the stats, economics, you know, you've talked about anything in the analytics space, and we don't just do data science, but we do data engineering, and product engineering training for all these folks. And it is a rigorous training program. You know, in the six months, four to six months that they go through, they have to even do a capstone project, it gets reviewed, they get feedback, there's a lot of effort, there's like a easily a 12 member team, that's putting effort in training. Right, so this is for people from campus. For people who are in the ecosystem, you know, part of their goal every quarter is to learn something at any point in time, right? So, you know, because a goal is defined and it is measured at the end of the quarter, it becomes a question that asks by the manager, people put an effort, right, and we recently launched our learning management system, which is learn with Coach, which primarily, you know, you can do self paced training, right, you can define how often you want to do it and complete milestones on the platform and complete your certifications. Right. So that's the other thing. Coach has a variety of other programs, right? You could, you know, you can learn on your own from home, you can, you know, create your own group and learn on a particular topic. You know, you let you come back and say, You know what, I don't find any of the training programs that I want to learn here. We encourage people to go and get certified outside and come back. Alright. So you know, there is a lot of investment that we do in ensuring people upstate Actually coach measures, learning, you know, learning learning outcomes outcomes of our everyday and our organizations, there is a measuring scale, if you look at it, where, you know, we measure how much people have upskill themselves, and it's a it's a metric that is tracked on a quarter on quarter basis, right. So the coach team asks the managers and finds out okay, as the, you know, capability of your team growth, if not, what should we be doing differently? So there is a constant, you know, leverage and upskill that keeps happening at math
company. You know, one one very interesting point. Ashish over here is usually I think, I mean, if I'm not wrong, 85 to 90% of the companies would have l&d as part of their HR team. And l&d is, I mean, I don't know, I honestly, I've not seen, or I've not heard of a company's investing so much day in and out in helping the employees grow, along with the organization in helping the organization's grow, or the employees grow. I've never seen such kind of an initiative or such kind of effort going, going towards the people development. So Ashish, according to you, I mean, coming to the mentoring and coming to the coaching, and coming to the skill sets, according to you, what are some of the top skills in demand possibly for or it's gonna be in demand, possibly for next two to three years? in deep tech space?
See, this is my my knowledge based on my interaction with business and what I'm seeing, I believe, Ai, ml, data engineering, maybe cloud computing, cybersecurity blockchain. So based on my reading, and what I see, I think these are some of the areas that are going to be top, you know, people will be looking for, especially engineering, you know, is very, very hot. You know, from a relevancy from an organization standpoint, I think AI ml and data engineering are some of the key skills that we are we are specifically hiring or pieces.
Right? So I'm in my sense, in my viewpoint, a plain vanilla baytech program, or a plain vanilla graduation program would not yield so much of result as much as creating a sub specialization for yourself.
No, no. So it is a base. So because I, you know, I think what engineering does is the ability for people to start thinking in a structured manner, breaking problems down. I think those are the skills for sure that people are learning today that they get an engineering, but I think what becomes more is okay, now on that base, what more can you build? right to be able to be productive industry? Right. Be able to contribute? I think that is going to be critical. Right? So absolutely. Engineering is a baseline. I don't think that's not but now, on the base, what more can you build to become a profit you have to focus on.
So maybe creating a niche for yourself and creating a sub specialization for yourself
is key. Yes. Okay.
Great. So Ashish, coming to my last question, what career advice would you give to someone who's looking to enter the analytics or data science career path? I mean, see, our analytics and data science are hot words are kind of high in demand, and everybody's talking about so what is what are some of the career advices? Or tips would you give us give them who are aspirants are data enthusiasts?
Sure, yeah. I'm not getting into the technical because technical is something I think people will figure out and learn right? Yeah. Yeah. And spend time on talking about more software aspects right. So the ability to tell stories is very important, you know, context and breaking down the problem and explaining it is very, very important to any audience that you talk to that's number one, number two, I think is the ability to solve a problem right. You know, people could say that you know, you have years of experience and your knowledge and knowledge is important, but having your feet on the ground and when the rubber hits the road the your ability to think through a problem right and apply the right mind and you know, is important extremely right. You need to be a giant, fail fast. Move on right. You cannot get stuck. Right? The moment you are stuck then you are in a you know sinking sank, right? You will never be able to get out right? So I failed, okay? Doesn't Move on, right? And I give this classic example. If you look at Children, Toddlers that is trying to walk, they never give up. Right? So they will fall down, they will get up and they will walk again and again and again till they get it. Right. Right. I think that attitude is extremely important. And I, I tell you that there's no way that it can that can ever change. Right? And I think Lastly, the adaptability. I think, you know, not saying I will do you know, I remember, you know, these are, you know, times when analytics was still early, early. And this is mostly a reporting, right, if something has happened, let me report it. What has happened is what, when, right, modeling was very rarely done, right. And I had people come back and tell me, you know what, I've done everything possible. In my project. In three months, I've learned everything I know for sure will commit me three months, I spent the project I've everything, I got it right, what next? What do you want, I want to move on to what I want to do modeling work, right? I think that, of course, the world has changed, politics has changed a lot more since then. But I think you're saying I'm not confined to doing only one like I'm willing to go, the whole breadth of things is what is going to be important for you as any for any individual, right? Don't be specialized early on, don't say I will do only this or only that, you know, you're have an open mind, explore different things. Because as you when you grow up in your career, you do not know how some of them can be used, you know, in your way of when you are a manager, you know, some of these will help you to become a better, you know, manager and professional to guide people all of those as well. Right. I think those are my four or five pointers that I wanted to share.
Thanks, Ashish, for setting sharing, Ashish. So while this is just, I quickly wanted to check on that while while the team evaluates people who have been in different multiple roles or identifying participants for different roles. I mean, when you kind of evaluate them, how important is a project work? I mean, is that one of the areas where you evaluate them? I mean, how important for a student or for a fresher? How important is it to concentrate on their projects?
I think project is going to be critical, because it gives you a perspective how work happens, right? And I think where people generally struggle is their ability to explain a project, right? Most of their knowledge is limited to what they have done. And that is danger. Right? And you're, if you're in a project, you should know what's happening throughout that project, you should know from the beginning to the end, if you're limited to only a section of your project, then you know, you're you're not knowledgeable enough, right. So that Curiosity has to be there, maybe somebody else is doing it, but being part of Scrum cops are being part of the stand up meetings, where people are talking about the project and going and learning and being part of those, the entire project process is extremely critical. So end to end project knowledge is important. And that's something that is generally asked right, if people come and say, we know you know, I did only only you know, eta, or I did only you know, structuring the problem, or I created only decks is limited to your growth. Right. And some organizations may give you the opportunity, some organizations may not but I believe as an individual, if you really need to know the impact that you've done, because of that project that you did. You need to know it through the end. Absolutely.
So yeah, I completely agree with that Ashish. And it's a strong word for for takeaway for all of you for all audiences. whilst you're still studying whilst you're still or some of you have completed your, your graduation or some of you're doing some certification programs, please remember project is the key Guys, please concentrate really well on your project. All right. So I think that's that's, I mean, I've covered most of the questions which we had curated. Now. I think we'll quickly go ahead and take the questions from, from our listeners from our audiences today. One interesting question, which which I can see from Ankita Patel, I don't know if she's still there. She asks, I'm pursuing B tech with computer science and is there an internship or are there internship opportunities to study frame it well, are there internship opportunities or does bad company look at internship opportunities, extending internship opportunities to these
folks? So folks, I think a lot of questions do you have openings We'll try and cover our entire hiring process and also talk about where we hire from on a regular basis. So one we go to campuses, we visit campuses, there are a bunch of colleges that we go to there are about 60 campuses that we plan to visit for the 2022. batch, you know, process have already started. And the plan is to onboard about 300 people next year. Right? So that's okay. Our campus hiring process is pretty straightforward. People go through an aptitude test, we have, we do something called as a video case study round, where we give you a topic you talk about it, and based on that we shortlist you this is to, you know, cover up for the group discussions that we used to do in colleges, you know, sitting together, and then you have our tech interview, which is when I say tech interview, mostly, or whatever I spoke about, you know, problem solving, structured thinking, puzzles and stuff like that. And then there's a fitment interview, an HR round, and that's it. So that's a campus hiring process. So for the colleges that we go to, there are some most of the some of these colleges have this option of six months internship. So for the candidates that we offer, we give them like a five to six month internship opportunity, which starts from say, anywhere from January, all the way till about June, and then they join us as full time employees. Right. So that's the, that's internship opportunity that we give them. And of course, everybody else, you know, joins us in June and September, spirit over the year is the president. Now, this is the regular campus hiring process right now, for folks who are keen to, you know, you know, join the math company, we do hire from organizations like talentsprint, who have gone through analytics training, right. So we we work with some of these Institute's and the best way is to, you know, enroll in some of these organizations. And, you know, we'll reach out to them and we will go through the similar hiring process with them as well. Right. So your opportunity to get to the math company has to be either through campus, if you're a freshman, I'm assuming most of the folks in this group is about zero to three years of experience. Yeah, one is through, you know, you know, coming directly from campus if you're visiting our college, if not, you know, joining organizations like talentsprint wherever analytics courses are offered, and we tie up with these Institute's and hire people from there.
Great, thanks. Thanks, Ashish, for answering to that question. One of the questions is, I mean, do MTech students are are to reframe the question are m Tech students eligible for any of the opportunities? I would do you guys look at MTech Chi Chi as
good questions. So I'm not saying no one yesterday, we've not done in tech so far. But I think what we are trying to do is there are a lot of colleges today offering like a sandwich program like btech MTech together in detail. Yes. Like this. So that's something that you certainly experience experimenting with. Yeah, so to put the question forward, based on whatever you asked right now, I would say yes, but are we hiring everybody else? No. So I see questions like is MCA considered? We considered as long as if you've gone through analytics training program? We don't put any restrictions there. Absolutely. Yes, we do. We do hire. Right. I'm seeing questions like MBA it Am I eligible because I, we go into a couple of MBA colleges, but we've not opened it up. It's, it's a, it's a start for us this year. We're going to specific MBA colleges to hire. But like I said, anybody who comes through any of the athletic schools? Yes, we will certainly look at it for 2021 based on the questions that I'm asking right now, I'm seeing right now 2021 we have done from campus hiring. But you know, if like I said, again, any LD schools, yes, even higher location, I'm reading out whatever is coming in front of you. So because, you know, feel free to chime in location. We are Bangalore based, but right now, we are all working from home permanently. That's a decision that the math company took last December. So you know, out of the 650 700 people that we have, most of them are in their respective hometowns, very few people in backlog. Right.
Ashish, one question. I don't know if this is the right platform to discuss this. But can you tell the difference between deep learning and blockchain?
No, frankly, I may not be the right person, right. Yeah, yeah.
Okay, actually so one another question which which I wanted to check. So for example, if there's a btech student in a blood say a third year, third year B tech student and if they wanted also these third year B Tech students go for summer internship for about three to six months and then endure In the fourth year and they are converted, most of them get a PPO and then they're in after the completion of their program, which is in fourth year, then they join the organization. So are such kind of opportunities also available. I mean, they do summer internship with you three to six months and then after completion of the program, they join you full time are those opportunities also kind of available or open?
seem like the based on the trend that I've seen and what I've seen across colleges so far. Most of the we would prefer to do them last trimester or last semester or the six months that we all talk about them, they have an opportunity to do internships full time, it doesn't then they do there is no break. So they do their internship and then they start work immediately right. So that becomes an easy process for us. If people are getting opportunities to do internship in three in their third year, I believe it is for a very short duration that is not helpful for us. Right. Right. So and like I said, the internship opportunities extended to people whom we have offered at campuses and not outside of that.
Understood. So this one question is by sreenivas, I kind of wanted to address to it, why the companies choose only B Tech graduates, even though they are from different branches, but Bs, CS, and MSC computer sciences are neglected. I mean, not not specifically from bad company, but like basis, your previous or past experiences, do you think you could help answer to this question?
Yeah, because I just think it is scale, frankly, right. Like, if you're a college specifically, when we're going for engineering students, there are BSc candidates available. I don't think it's a no. But I think because of scale, and wherever I wherever your hire a lot of people, I think engineering GaNS are the easiest to find. Right. And the number of B BSc candidates are lesser is what I feel. But like I said, having, you know, anybody who's gone through an analytics course, or a program more than willing to try and experiment, you know, to take them into our ecosystem. And today, there is no restriction from anybody who's going through an analytics course and we find them relevant suitable, we generally hire BSc MSC MCA doesn't matter. I see a lot of questions about MCA who knows Mike, you know, programming? Absolutely, you know, we would love to hire you guys. If you have done gone through basic analytics, right? Because the the opportunity for there's no time for me to curse, you know, train you after coming back into my current microsystem. So I would rather have you trained, and then you know, made available.
So I would just quickly like to sum up to, I think, to all the eligibility questions, which are coming in if this stream is eligible, or if that stream is eligible. So I'll just just quickly sum up what Ashish just said. If you are in it doesn't matter, which which graduation specialization you are from, provided you have created a sub specialization for yourself or provided you have been trained in an analytics space. You You can justify your your your certification, you can justify your your need to be in analytics, I'm sure the math company is open to evaluate you and to look at you for all the opportunities available at the mark company. So one question is I am an MC a final year student and I'm learning about Python Django. So is this Django demand in the market? Or is it there?
Yes, yeah, it's there. But like I said, right, it you cannot look at it and only as siloed right, it has to cover other data engineering concepts of being exposed to the cloud architectures on so you can't learn Django alone and get into the math company, you need to be a more well rounded data engineering professional as well. Right. Right.
And how about in terms of so I think now, another question in terms of marks, do you I mean, see most of the companies like like most of the system, integrated companies, if I have to say like TCS is the likes of all the system, integrated companies, they they look at 60% throughout kind of, I mean, no matter how strong you are, they they look at 60% throughout, so is bad company, also kind of looking at 60% throughout kind of criteria.
That's a general guideline that we've set for ourselves. So 60% with no backlogs is what we have put. And it's just a baseline. Right? We believe generally most of these folks who are in engineering colleges, I'm sure must be a minimum of 60% and above, right, but if you have backlogs, then it becomes a challenge because I'm going to Give you an offer. And then you know, if you say at the end of the you know, your graduation, you're saying I have backlogs, I have two papers to complete. You know, it's a space taken where I could have probably hired somebody else. Right. So it's only that we don't look at 10th and 12th marks, which is mostly look at your grad marks is where we insist on 60% above with no backlogs. I'm just answering the question that Donna just asked on the chat.
I think now the questions are quite, I think on the same lines in terms of the eligibility criteria, and the marks and stuff. Any other questions, guys, any other any other questions you want to know specifically about? Maybe the math company or maybe about data science? How can you? How can you learn more about data science? How can you learn more about data analytics, data engineering? Any other questions on those lines? I think we have covered the eligibility criteria part. Any other questions on those lines?
Okay, a cloud company? Join talentsprint?
Yeah, that's that's a great question.
So some of you guys asked about guys, currently, there is no off campus, plan for at least 2021. You know, if you want to know about openings at the math company, please visit our website, all the openings are visible. And please apply to the relevant opening. That's why you can follow us on you know, LinkedIn, Instagram, we are you know that a lot of articles we keep publishing on a regular basis. So please go ahead.
So what's the trend? Now there's one question by the ninja what's what is in trend now, a programmer or a data scientist?
Frankly, I don't know the difference. I think both are the same. or the other. It's just what do you call it? It's terminology. Like the other day, I was talking to somebody and I said, the designation is going to be analyst and the person is taken aback and said, Are you sure that's the right designation to give somebody who's a data engineer? Frankly, it doesn't matter. When I started work, at least with an IT services company, which is Taiwan, you know, they were called business analyst. And, you know, business analyst as a, I, at that point in time, were people who were interacting with business and, and the, you know, and the company, bridging that gap. And that role has evolved. So much like in music, my initial designation as a business analyst changed completely right. So frankly, title doesn't matter, guys, you know, designation is just a name. But what you do is what is important? At the end of it, you need to know, technology, you need to do business, to be able to do when,
right, to answer one of the questions Raghavendra. His question is Raghavendra tops. Question is, Are there enough resources for data science learning? Absolutely. Rather than driving? There are enough resources on LinkedIn on YouTube on? I mean, they're absolutely I mean, if you just go on LinkedIn, you'll find people are happily sharing information about data science, or happily sharing about information about analytics. So there there are ample information, you just have to go and find it out. Yeah. I think most of the questions I think we have covered most most of the questions. And somebody has asked that you are introducing about math company or you're talking about the math company the presentation, like for the next five minutes, do you want to show that or not? No, I
can I for those who came in late and who missed my introduction about the math company. So we, we are primarily, you know, a global analytic solution provider, we focus on helping organizations to build internal capabilities assets. For in analytics, we we build custom Product Solutions in their environment, so that organizations are able to, you know, solve their problems on a regular basis. Like I said, we're five just going to be five years old. We are going to celebrate our anniversary next Friday. We are about 700 people strong across the globe. We are domain industry agnostic. So we work across, you know, retail CPG pharma technology. It doesn't matter, any of any of those areas. We work with about 50 of the Fortune 500 organizations. You know, we we've been awarded as one of the fastest growing AI ml Organizations, both in 2019 and 2020, by delight, bunch of awards that we have received, founded by three folks, Cheyenne or not. And Aditya, they have easily about three and a half decades plus years of experience in the analytic space. All three of them have worked in, you know, different industries, domains, across across organizations as well. And yeah, I'm saying, you know, our growth has been tremendous in the last two years. COVID. year we doubled. The plan this year is to touch about 1000 people by March 2022. Yeah, and the past four groups. Yeah. Anything else? Any other specific questions? That has come up? I'd be more than happy to talk about.
I think one one is slightly different. So this is by overnight only permission, Ernie, I have completed Salesforce platform developer, one certification. So I mean, does Matt company look at those that skill set?
No, not Salesforce. I'm sorry. Yeah. So I saw some questions around, is it a good idea to switch, you know, career at this point in time. So guys, you know, jump into it, if you're ready for the learning experience, and the growth. This is the next big thing. Now analytics industry has been in existence for more than 15 plus years today, and it's significantly growing. And it has evolved from what it was, you know, your, you know, 15 years back to what it is today. Right. So, you know, don't switch just because you know, it is the next big thing, but you have to be ready to learn, you know, go, you know, there a lot of unlearning that needs to be done here to be able to learn what you have to do. Right. So if you're in for it. Yeah, go ahead. You know, this is the space to be in. It's the next big thing. Okay, what?
I don't know if we have covered it or not, but I'm sure most of you have covered it. But what are the skill sets that can help to work with? With the Mac company? This question is, I think from vignesh sure, that the skill sets that can help to work with the math company.
Yeah. So we had covered this in the past, sometime back, but I think one I had spoken about was the attitude, the intent to learn, the willingness to go the extra mile. That is important. I think the capability that you need to build for yourself is, you know, the ability to tell stories, the ability to bring down a problem, the go getter attitude, I think I can I can keep talking about all of these. But I think, you know, your attitude is what's far more important in this space. And saying that, you know, I will do whatever it takes to, you know, Lord, and go the extra mile.
Okay, awesome. Thank you so much, Ashish. First of all, congratulations to the map company team on completing or on or about to complete five years. Everybody just haven't gone actually, at the map company. And, of course, I would, again, like to thank you, Ashish, for joining us today and sharing all the amazing and informative insights. We really hope to do this again in the near future. Sheesh, yes. Any last words to all?
No, that's because thanks for organizing this. It's always a pleasure, talking to people. I wish it is more interactive, I see a bunch of questions. I'm hoping that most of it has been answered. I think my only parting words is guys, stay hungry, you know, hungry to learn at every point in time, you know, willing to take risk is extremely important in this stages, you know, never, never get into your comfort zone. The moment you've got into your comfort zone, Be rest assured is your toe. So you know, always be, you know, I'm not saying you know, you have to always keep taking the risk extremely, but be uncomfortable, do or, you know, try and learn new things. That's the only way that you will be able to be, you know, leveraged in this industry, right, and to be staying alive to being relevant. So to be relevant, you have to be in the uncomfortable. So
I guess the key takeaway of the session be uncomfortable guys, after thank you to all the participants for joining us, and we really, really hope you got some key takeaways. One is, of course, be uncomfortable. from today's session. Stay safe, everyone, and all the best. Thank you as you guys take care. Bye, everyone. Thanks for coming.
Watch the entire interview here https://www.youtube.com/watch?v=jtnVe0dk1pk
Note: This video transcript is generated by AI. Therefore, it may not be 100% accurate.