SOUTH Africa-based Zindi, the first and fast-growing data science competition platform in Africa, hosts an entire data science ecosystem of African scientists, engineers, academics, companies, NGOs, governments and institutions focused on solving Africa’s most pressing problems. In a recent conversation with Africa Briefing, CEO Celina Lee outlined the importance of having a platform like Zindi.
This interview has been edited for length and clarity.
Africa Briefing (AB): Can you tell us more about your platform?
Celina Lee (CL): We have a community of data scientists from across the continent, 50,000 data scientists that have joined the online platform and are using the data science skills, to learn artificial intelligence to solve problems for companies. And as a by-product they are just really meeting each other and connecting with each other to learn new skills and even find job opportunities on the platform.
AB: And how would you describe data science to the uninitiated, or, can I say, the uninformed?
CL: Data science – it’s a new field so people are not so familiar with it It’s existed for some time in different forms. It’s a form of analysing data that is extracting real value of business, getting real impact out of the data access that companies have so that digitisation that we’ve seen in Africa, there’s really been a leapfrogging where companies are dealing with massive amounts of data – customer data, satellite data, transactional data – that’s all being digitised so that now the question is: how do you use data to make better decisions, to even automate some of your services? So data science is really the science of data analysis taken to another level where you’re dealing with much more data and much more sophisticated algorithms to help you develop new services and value.
AB: So that means that these days just about every business entity, government services… they all use data science?
CL: Yes, any organisation that has data probably uses data science. And just to give you concrete examples. The types of challenges that we run on Zindi, which are data science challenges, can range from very familiar things for businesses like predicting customer return, product cross-selling where any business has multiple products, which products should you offer to your client, to each specific client, fraud detection, demand forecasting – these are all standard problems, but what’s much more important is we’re dealing with much more data, much more computing, much more sophisticated algorithms. And then there’s more advanced, more complex cutting edge applications which can be things like natural language processing, so looking at a local African language tweets on social media and being able to develop algorithms to understand what these tweets are about. Are they positive or negative, what are they talking about, or even translating them into English or French – this is also data science as well.
AB: Can you also tell me the importance of also having a platform like yours, or creating a community for data scientists?
CL: Well, we like to think that data science is a team sport. It’s such a quickly evolving field, it’s a new field, it’s a field where very few programmes or universities offer programmes in data science right now so it’s very important to have a community, it’s very important to have a place where you can connect with other people working on the same types of problems as you and where you can learn from them, as peers. You can also connect with people as mentors. So community is incredibly fundamental to any data scientist’s career journey.
AB: So right now, how would you describe Zindi’s business model, as you are operating now?
CL: We run challenges on the platform where companies can essentially put up their data sets and problems and then have up to 1,000 data scientists working on your problem and competing to build the best solution. You get the IP from top three solutions that come out of this challenge. That’s one. Secondly, we also offer recruitment from our platform, so that we have 50,000 data scientists across 51 out of the 54 countries in Africa. We have 26 percent women on the platform and a lot of companies are interested in how they can recruit. And then third, is this idea that a lot of companies are interested in putting their brand in front of our community to make sure that this community knows about the latest data science tools or resources that are available to them or even career opportunities in some of the largest pan-African brands. So it’s a combination of those three things – solutions, talent and brand awareness.
AB: How do you go about acquiring and retaining clients?
CL: The clients that we serve fall into three main buckets – we work with the global tech giants like Google, Microsoft, Nvidia. Secondly we also work with the large African corporates, so the big banks, the telcos, consultancies, and then we work with starts-ups – both African and global. How do we attract them? A lot of it’s by word of mouth and organic growth so far. We’re really starting to build an awareness of Zindi as the ecosystem for data science in Africa, so a lot of companies come to us when they’re looking for any of these values that we deliver.
AB: How long has Zindi been in existence and how fast is it growing”
CL: The platform launched four years ago. It’s been growing quickly by 100 percent year-on-year in both the users and on our revenue. And the monthly active engagement on our platform has more than doubled in the last six months.
AB: So far, how does your team define product market fit? And if not, how soon do you hope to achieve that market fit?
CL: We have two audiences that are very important to us – the data scientists (50,000) and then there’s the companies that work with us. So those are two different audiences we obviously need to find but in one product. And that’s what is so powerful in Zindi because we have deliberately focused or prioritised finding market fits for our data scientists – first to delight them, to give them real value in terms of their career trajectory, their skill, their networks, all of that. And in essence, in a way we’re building like a LinkedIn for data scientists, plus a lot more, so that you can build up your skills. So I feel we are very close to finding product market fit in our community. We don’t, we hardly spend anything in marketing, most of it is word of mouth. Our user acquisition and engagement has been growing month on month.
Then on the client side, our product market fit is really about the companies being, like their pinpoint being solved by what we have to offer. And we’re finding that probably the biggest pinpoint or the thing that we’re hearing most is about the scarcity of talent on the continent. That companies like ABSA. ABSA is one of our strategic partners, so for these corporates we mostly focus on selling annual strategic engagements where we combine all of those values, where they can get solutions through the platform, they can get ta
lent through the platform, they can get brand awareness through the platform, but the biggest pinpoint for them is the scarcity of talent and that Zindi is able to deliver.
AB: What is the scale story of Zindi as a business and also from a commercial perspective?
CL: One – we are the community for Africa, and I think that there are so many opportunities and also challenges that the data science community in Africa is solving, that we’re helping to create this platform – where we’re creating opportunities, creating the ability for this talent that wouldn’t have been seen before and also uncovering and building new value to the market. I think that’s what’s really important. And I do see that other emerging markets, whether it’s the Middle East, Asia, South Asia, Latin America – they’re faced with similar challenges in terms of access to skills, access to talent, access to networks. So one of the things that we’re really excited about is – the axial story for Zindi – would be an emerging market player, a global player.
AB: Who are your biggest competitors currently?
CL: There is another data science platform that’s global called Kaggle. They’re based in the United States but they have a community of I think 8 million users so they’re massive. They’ve been around for over 10 years and they were acquired by Google a few years ago. They’re really big so in a way they’re a competitor of ours but I think there’s a pocket in the emerging market that has been left out of their story and we find that a lot of our data scientists in Zindi, maybe they’ve tried Kaggle but this place isn’t for me, or these datasets don’t even factor into what I need to be able to do when I get a job, so they’re a competitor but they’re not. S
o on the data science side, their experience on the client side, literally some of our clients have tried to approach Kaggle but Kaggle says no we’re not interested.
AB: So, would you describe Zindi as the only authentic African company of its kind?
CL: Yes, we’re the only African company of its kind. We’re the largest community, we’re the only online community of this kind in Africa.
AB: What would you say are the biggest obstacles that you’ve encountered so far as a business?
CL: Can I say something about the last question, there’s one another thing… Because I think other competitors in a sense could be recruiters or traditional recruiters or maybe some of the recruitment platforms and I think that something important that Zindi is doing is that we’re not just helping companies find talent in the existing pool but we’re expanding the pool because we’re creating more skills in the pool.
We’re also uncovering individuals that wouldn’t have a platform otherwise or know to put their resume on to some of these recruitment platforms. And then on top of it, because we’re running these challenges all the time and people are building up their professional profile where they can say ‘I solved a problem for Microsoft, I solve a problem for Uber…’ and it’s proven on the platform, it’s a much more powerful experience.
AB: So now we go on to the biggest obstacles so far…
CL: let me think about that. I think as an African start-up you know the funding landscape is a bit more constrained obviously so we raised the seed round last year, we’re raising another round right now and I think the economic situation right now is obviously constrained. But even under the best circumstance I think for African start-ups, we struggle a lot to find VC’s that are willing to take bets on plays like this. I think that’s one and then I think that one of the challenges is just that data science is still a new field but that’s also an opportunity because it’s wide open and there’s so much excitement about it, but the talent pool we have is very young, a lot of the companies that we talk to are still in a somewhat immature stage in terms of their own data science journeys, so there’s challenges but there’s also huge opportunities.
AB: So you say you did a round last year. Can you tell me how much you raised? And how much you hope to raise in the second round?
CL: Last year we raised $1 million, and that was the seed round. And this year we’ll be raising $2 million as a seed extension
AB: Where do you see Zindi in 5 years’ time?
CL: I think the emerging markets play is huge. I want Zindi to be the place for data scientists, where they know that they can come and create opportunities for themselves and their communities, where they know they can meet other likeminded people, or where they can create new skills and find amazing career opportunities for themselves. I want everyone to have their Zindi profile as their new CV, their new profile that they can be proud of, that companies can look at and know that they’re choosing the right person.
