South African startup Zindi, has secured $1 million in a seed funding round to aid the expansion of its network of data scientists.
Zindi is a digital platform that hosts Africa’s largest community of data scientists. By showcasing the continent’s data science talent to the world, Zindi connects data scientists with organizations and businesses, providing a platform for data science enthusiasts to learn, develop their skills and get employment.
Launched in 2018 by Celina Lee, Megan Yates, and Ekow Duker, Zindi works to resolve critical challenges with the use of machine learning and artificial intelligence. The platform now hosts more than 30,000 data scientists, at all levels from novice to professional.
With registered users from 150 countries around the world, companies and businesses approach Zindi to source talent and solutions for their organizations. Zindi has almost doubled its user base since last year and has delivered about 100 machine learning solutions to clients.
The seed funding is to help further expand to the global market. Speaking on the expansion, Lee said, “We are a platform with African roots but global reach. So far, our main focus has been on penetrating the African market. We will be the go-to platform for every data scientist and aspiring data scientist on the continent. It is entirely possible that if we can get it right in Africa at scale if we can create a world where companies, data sets, and talent are seamlessly connecting on the Zindi platform to create new exciting value, we could replicate this model in other emerging market contexts where many of the opportunities and challenges are similar.”
“We already see, for example, data scientists from Kenya, Tunisia, and India who met on Zindi, teaming up to solve a problem for an organization in South Africa. We shared a frustration seeing companies in Africa sitting on unprecedented amounts of data and excitement about data science, AI, and machine learning, but not knowing how to even start. They often assumed that they had to look outside of Africa to find the people they needed to help them.”
Companies, on one hand, are able to unlock the power of their data, while people are able to pursue careers in data science irrespective of race, gender, or geographical location.
Zindi charges companies when they post a challenge on the platform, and then crowd-sources machine learning solutions to them. Challenges vary from customer churn prediction and cross-selling products to predicting flood extents using weather data. At the end of the day, the companies would own the IP of the top three solutions.
“We also make money in talent placement. We source top candidates with the right skillsets for companies. We are able to draw on the candidates’ actual performance and engagement on the Zindi platform.”