VP Product Movin Jain on always following the First Principles Thinking approach & how Meesho fuels his lifelong passion for solving tough technical problems
By: Amrita Bose
Tags: Data Science, Math, Culture, Startup, Problem Solving

VP Product Movin Jain on always following the First Principles Thinking approach & how Meesho fuels his lifelong passion for solving tough technical problems Amrita Bose Follow Nov 15, 2019 · 11 min read

If team Meesho gets monthly, tricky puzzles to solve over emails and candidates get asked tough Math questions during their interviews, we have only to blame Movin Jain — VP Product. Passionate about Math, Movin is famous/infamous for having made friends at Meesho with those who have been able solve his Math problems.

A BTech graduate in Computer Science from Indian Institute of Technology (IIT) Delhi and an MBA from Indian Institute of Management (IIM) Ahmedabad, Movin won an Honor for India at the International Math Olympiad in Mexico, in 2005. But his journey towards finding his true calling — that of building technology was a circuitous one. After his MBA, Movin started working in the world of finance at Barclays Investment Bank in London. But even though he achieved several career milestones as a Bond Trader, something was missing in his life. After working in finance for two years, Movin understood that tech was and always would be his true calling!

He then moved back to India and joined InMobi as part of its Marketplace team. Further stints included cofounding and running his own startup galleri5, a social media influencer marketplace and working at Ola Cabs as well. You can read more about how Movin found his way to being a techie here.

Apart from obsessing over Math, Movin is also a half marathoner, a budding pianist, a die hard U2 fan, and a self confessed Elon Musk fanboy.

Here’s Movin telling us more about why he loves to solve hard problems, especially those that straddle both business and technology, with lots of mathematical thinking and data thrown into the mix.

In my head, I had always thought that I was going to be a product guy. At InMobi, the functional boundaries were not well defined because it was still a small startup, so my role was part Data Science and part Product. Plus, the Indian startup ecosystem around 2013–2015 was still pretty nascent so job scopes were not very well differentiated. It was also at InMobi that Vidit Aatrey (Meesho CEO and co founder) and I became colleagues and friends. In fact, I remember when we were both about to leave InMobi, we had a conversation about starting up together, but I started up with another friend of mine. Maybe it’s destiny that eventually brought me to Meesho!

After InMobi, I cofounded galleri5 along with an IIMA batchmate in 2011. We started off by making a photo app like Instagram, where instead of following people, one could follow topics. An interest based online community of sorts with user generated content, galleri5 later pivoted to a social media influencer marketplace. While at galleri5 I was always the product guy and my cofounder the business person. We thought we needed a tech cofounder as well. But when after a couple of months of searching we couldn’t find a good tech cofounder, I decided to function as the CTO myself.

Once a coder, always a coder

At this time I had been out of touch with coding for four to five years. I thought I wouldn’t be able to do it,partly because of reluctance and partly because I was nervous. But as a cofounder when I was forced to do it, I realised how much I had missed coding.

Starting to code again was perhaps one of the best things to happen to me.

Because I really loved coding, I then did well as a CTO. But running a startup often involves focusing on operations and sales as well, and I was increasingly feeling like I wanted to be closer to tech, no matter what I do. I then decided to move on. And between Product and Tech, I felt I was more suited to product because I wanted to use my people skills, stakeholder management expertise and user understanding. And that’s when I started looking for product roles.

I then joined Ola Cabs, leading the Supply Shaping Product team there for a year. While at Ola my main career goal was to get experienced mentorship, I found that in such a large organisation, it was tough to make an impact at an individual level, and Ola’s focus at that time was more on efficiency than growth. That didn’t excite me much as a techie.

I was constantly looking to innovate and build things, and I needed to find a space that would allow me to do my own thing. And I think I finally found that opportunity at Meesho. Vidit himself, and a former IIMA batchmate and friend Ravleen Shravanth (VP Strategy to Execution at Meesho) convinced me to give Meesho a shot. Meesho’s strong product market fit and it having the backing of top notch investors, also convinced me further.

A tough cookie

My focus from the beginning has always been on solving tough problems. Tough problems excite me like no other. When I am doing something easy, I tend to lose interest. Over time I have had a tendency of gravitating towards tough problems and having a good ability to solve them. And these tough problems often tend to be technical problems.

At Meesho, what keeps me awake at night is personalisation and search — two rather tough technical problems, which I am constantly trying to solve.

When I joined the product team in 2018, it had five members, including me and the engineering team was about 12–13 people strong. It was a great experience of teaming up with a small but smart bunch of folks, who were working on a problem they were very passionate about. I had witnessed for the first time a team that was so closely knit, so hardworking and that so clearly understood the problem they were solving. Initially my role wasn’t super static and I found myself (as a lover of solving tough problems), being instantly handed over some burning problems, which needed immediate attention.

Owning it

Movin Jain at a panel discussion organised by AWS on Building Around Recommendation Engines, Fraud and Forecasting

Once I had settled in at Meesho, I took ownership (a core Meesho value) and executed a few projects successfully.

One of the first things I solved for was Taxonomy. Earlier we didn’t have a proper classification of catalogs on the app. As a first step to personalisation, taxonomy is important. For example, which saree on the platform is silk? Until you know the details of the fabric, you wouldn’t know what kind of saree a reseller likes and there was no way to record that before. When someone opens the app, they see what they want to see and in Meesho’s context they see what their customers would want to buy. If data tells us that someone has been ordering mostly silk sarees, then the app will show them silk sarees. And to do that, we first needed to have a record of what is a silk saree and what is not.

Even when we onboard catalogs and suppliers everyday, we don’t know which ones are good and which ones not. To make our resellers successful (a core Meesho value), we have to showcase the best catalogs to them. Among the new catalogs, we don’t know which ones are the best. For older catalogs we know the best products because we have data for them. But if we keep relying on the old catalogs, then over time we will lose out because our resellers would want newer, fresher choices.

In Data Science terms, we call this an Explore versus Exploit theory. You exploit your old products, but you keep exploring new choices too. I took ownership of ironing out some glitches of an already existing system that handled this Explore versus Exploit Tradeoff, and made it better.

Another successful project that I worked on was launching the Image Search feature on the app, based on anecdotal data we gathered from our users. Launching Image Search was one example of solving a tough problem that gave me the thrill I’m always looking for. It was also one of the core use cases of AI (Artificial Intelligence). Being good at Math, I had always wanted to work on AI and ML (Machine Learning), but it was hard to find a real world use case for something like this. Rather than writing academic papers on the subject, if we are able to help the average joe, and make resellers successful by helping them earn more and delighting their customers, that is a big win for me. With image search we helped the reseller give the customer exactly what he/she wished to wear or buy. We also improved upon the existing Text Search algorithm.

Making AI accessible to the common person was a huge win in my mind and was in line with my own values and the reason I joined Meesho.

From left to right: Movin with a Product intern and a team member

I also played a role in setting up a smart Data Science team at Meesho. We wanted to graduate from an elementary stage to an advanced one as the scale of our data was also exploding because of Meesho growing at a hectic pace. Hence setting up a good team was imperative!

One of the biggest things that I have learnt at Meesho is to always take a First Principles thinking approach to a problem.

The First Principles approach says, always start from the point where you assume that you don’t know anything. Don’t rely on what’s been done already. The objective is the only thing that should matter to you. From there on, go with an open mind and come up with your own solutions, rather than depending on what has been already done in the past. Because Meesho’s business model is a new kind of business — a new use case altogether — we had to forge our own way.

While hiring also, this is one of the things I always look for. Lot of people in Data Sciences don’t have a fundamental understanding of Math. This is something that intrigues me, as to why we don’t have more people good at Math working in business. Because if they did, things like personalisation would be much easier to solve. Even though a lot of research has been done on personalisation, writing an academic paper versus actually implementing it in the real world are different things altogether, Very few have actually gone into practical application. In the world of ML and AI today, there are many with strong Math fundamentals, who are doing research. There are also many who are working on practical applications, but may not have strong fundamentals in Math. There are very few people at the intersection — those who understand Math, and want to practically apply AI and ML in business.

So, if you are like me and want to apply Math in the real world, but so far haven’t found an opportunity, then you need to write to me immediately. Because I have been looking for you!

The value proposition

The Meesho value of Hungry to Succeed resonates quite a bit with me. And here I would like to connect the First Principles approach to it again. Being in the esteemed company of colleagues who are equally hungry to succeed is infectious. It infects me with the same drive and hunger.

I don’t think I was able to achieve what I was made for until I joined Meesho.

Hungry to Succeed is something I learnt to live right here at Meesho. And it also trickles down to my hiring decisions — every person on my team needs to be Hungry to Succeed. Being Hungry to Succeed makes you come up with solutions that are innovative, which also means breaking convention. When you are hungry you are always trying to figure out how to achieve an outcome in the fastest possible way and that’s when the First Principles Thinking gets forced on you because of your burning desire to succeed.

I also imbibed the fine art of Speed over Perfection (another Meesho value) after joining the company. Always pick the biggest problem first and solve it first. Don’t pick a bunch of small projects to do at the same time. Focus on one thing and master it. And do it better than everyone else. And then move on to the next problem. Try and ship the MVP (Minimum Viable Product) or the core of your product idea in the fastest possible way.

When you are building something new, the most important thing is not for your first idea to succeed, but for you to be able to find out quickly whether it will succeed. Because once you know that it won’t, you will iterate and eventually get to something that will work!

So, if you are already too deeply married to the success of what you are launching, you will end up trying to make it better and better before launching, and this might take forever (something I learnt the hard way at my own startup). You have to detach yourself and take a step back. You have to first validate your idea, and assume that the market knows more than you. Be open to listening to what the market is saying about your product. Once your objective is that, then you will automatically start figuring out the most important things you will need to ship in Version 0.

This thinking is a way of life at Meesho. Let’s recap one more time.

When you have a new idea, ask whether the market will react positively to your idea or not. Don’t assume anything, launch with the minimum set of features and find out the answer. Once you know the answer, go all guns blazing to make your product better, to make it bigger and bigger!

And lastly, don’t forget to celebrate every win. At Meesho we love to celebrate every launch, big or small, by getting together and having some fun.

Want to challenge Movin over Math puzzles and help Meesho create 20 million entrepreneurs by 2020? Then apply here or send him a message on LinkedIn. We are hiring!

And if you want immediate gratification, below are a couple of puzzles handpicked by Movin. Feel free to reach out to him with your answers or leave your answers in the Comments section below.

Puzzle 1

The vertical red line is perpendicular to the bases of the three semicircles. What is the area of the region shaded in orange?

Puzzle 2

What percentage of vehicles in Bangalore, are such that their license plate’s 4 digits are in strictly ascending (increasing) order, as you read them from left to right?

Points to note:

1. For the digits to be strictly ascending, it’s necessary (but obviously not sufficient) that no two digits are same.

2. We are talking about the numerical digits that occur at the end of the license plate (e.g., 1257 in KA01MK1257)

3. Leading zeros (0014), and all four zeros (0000) are valid license plates. In fact, 0137 is strictly ascending too.

4. Assume that the authority allots these registration numbers randomly from a uniform distribution.

All the best folks!