We sat down with Rishi Kumar, Pollen’s VP Data, to find out about his career at Spotify, curated data experiences and his advice for an impactful career (hint: play the long game).
Pollen: First up, what’s your role and what does your team do?
Rishi: My role is VP data, so you could say I'm responsible for the value contribution of data and we actually have a few teams.
One team is the data platform team and their job is to collect and protect data and a team of analytics engineers whose job it is to make that data easy to use for learning.
Then there's the team of analysts, whose job it is to enable self service learning. They create the visual language and the interactive dashboards for teams so that people can see information on a screen and process it.
We want everyone to be able to find and process the information they need without the direct support of a data professional or an insights professional. We are shooting for true self service in that way.
Tell us about your career before Pollen
I had a kind of long run as a data scientist. I started at Unilever in 2005 before data science was a job title, working in consumer goods. I automated my first job doing reporting with VBscripts and after that I would just walk around and try to use my data and math skills to be helpful.
After a few years, I went back to school to do a master's and kept my job part time. Then at the end of my masters I got this email from Unilever's head office saying, hey we heard you understand data, and you know a little bit about our operations and we've got all this data around the globe, can you help us make good use of it?
I thought oh, this is such a spectacularly blank sheet of paper with an awesome objective, and so I spent the next five years in the head office trying to build data science and analytics as a capability for Unilever around the globe.
I realized to get the experience I needed to grow, I needed to go into tech and get some street cred where there's much bigger data sets and cool technologies. So I left Unilever and with some colleagues from Unilever started a company called eBench, which was reverse engineering digital marketing strategies and that was really cool. During that time I also helped to set up a bunch of data science teams and capabilities at other companies and one of those companies was Spotify.
When I decided to leave eBench, I sent an email to close my contract with Spotify, they were like well hold on, we think we've got another blank sheet of paper for you.
And it turned out that they had all these data scientists, they’d gone from 10 to over 120 in the blink of an eye, and all of a sudden, they had a lot of scaling problems; shared practices for data scientists weren't quite there and data wasn't managed to make it easy to produce insights.
So I got this awesome job as Director of Data Science Practice at Spotify, where I was helping to improve efficiency and effectiveness, identify and remove pain points for data scientists. And I got to know many of the very, very talented and awesome people who work at Spotify – one of which was actually Alex Varia (now VP Insights at Pollen).
And what took you from Spotify to Pollen?
The last company I worked at sort of popped because of COVID. I had decided that I wanted to join a company with a great purpose and culture, somewhere I could stick around for a while, you know, and have a stretch of building data capabilities. Somewhere to really contribute to a mission I thought was great.
And that's when Alex suggested “hey I think this job is up your alley” and then the rest is history.
What is it about data at Pollen that excites you?
I think what I like a lot about data is the value contribution of it, the fact that it can totally change the way you operate. It gives you the ability to observe, understand, predict and ultimately influence the things that really matter to your company.
I like the idea that you can be scientific about anything you care about; you can try and exert influence around how well our experiences sell out, how well they're crafted and how good a time people will have.
I think that Pollen’s got an awesome real world problem of trying to help people have a really great, memorable experience and we can be scientific about that – we can be scientific about the experiences we provide, about our operations and cost – and it’ll be a competitive advantage for us if we are. So I think having an impact on the company's mission and building a data capability that is a really meaningful part of that is what excites me the most.
What are you really looking forward to working on with the team?
That's a good one, so we’ve been executing on giving people in Pollen the information they need just to make experiences happen. Now we’re focusing on curated data experiences for learning.
We’re going to partner with people and specific functions, and get to know their needs, what they see the value of their role is and their hopes and dreams are for it. As a company we talk about giving our customers curated travel experiences and we want to give teams working at Pollen curated data experiences.
We want teams to pick up these curated dashboards, to help them learn about their universe, facilitate their workflows and learning goals, and really do their job well.
For example, helping customer experience to understand how they can improve their customer satisfaction scores on their own.
And then there’s another area. We have a long history of perfecting our outbound sales, a kind of peer recruitment model for selling experiences for colleges. We have amazing relationships and partners who bring their community to these big artist-led experiences, but there's this middle ground of non-college, non-artist-led experiences. These concepts make Pollen really unique and we're starting to invest in the science of selling those things, crafting and perfecting those experiences. So I’m really excited about the learning goals we’ll establish there.
And that's a big cross functional effort with data scientists from insights and product teams and technologists. So that'll be really awesome and as we prove our success there, there'll be more curated data experiences to help people go on their learning journeys and have an impact on members’ experiences.
What is it about the culture that attracted you to Pollen
I wanted to join a company where Mastery was not just something that we support because technical people like data scientists and engineers really value getting good at stuff, but that is actually a part of how we motivate people. Of course as technical people we want to invest in our own development and at Pollen we really, really mean it.
In data I like how we formalize Mastery; we bring it into our job profiles, we have development champions we meet weekly and we link our quarterly goals to developmental goals. We’re bringing Mastery to life in a really meaningful way, because it's not a side hustle, it's about how we motivate people, how we expect people to show up and continue to put energy into their work.
I think Pollen adds a whole other level to culture by introducing this concept of belonging. I’ve got dyslexia, for example, and I'm a person of color and so diversity matters so much to me. Belonging in particular goes beyond these facts as it's not just about diversity, having representation, but about making different people actually feel like they belong – the idea that you can just be yourself at work. I want everyone in the team to feel like a culture add.
What advice would you give to someone looking for a career in data?
Oh the easiest advice I can give is to play the long game. To be successful in data, you need a combination of skills and in depth knowledge covering science and engineering, and then there’s a breadth piece about your ability applying these in a commercial context and knowing your industry.
I would say, spend time getting to know all different crafts from science like experimentation and machine learning, but also simple things like metric setting and data visualization. And then take some time getting to be a better engineer – good coding practices and understanding how to make the most out of different programming languages, how to store data cheaply and how to muster up compute resources.
Then try to find yourself in different domains where you can bring your skills to life in a commercially valuable way, consider learning about marketing content, maybe product insights and customer operations, definitely spend some time in finance.
All that is a really a long run right? So don't be in a rush, just take your time to have a career and be patient about it.