“Skills speak louder than degrees” — Daniel Bruintjies
Tech, research, problem solving and entrepreneurship, elements to his passion and also a backbone of innovation and progress. Meet Daniel Bruintjies, a data scientist who is thriving in the world where College degrees and formal education often take center stages in achieving dreams. He believes interpreted data holds great value and enjoys using extracted value to solve problems across various industries.
Humble beginnings
Daniel, a Cape Town, South Africa native, took his first steps in the world of data because he wanted to learn about data analysis methods and statistics that could be incorporated in his entrepreneurial pursuits. He got into the engineering program at a university in Cape Town, but unfortunately had to cut his formal educational pursuits short for personal reasons. Instead, he joined Explore AI academy — a practical one year training program where he was introduced to Python, SQL, data analysis and machine learning. He came to love working with data and developing machine learning modes. After graduating, he found joy in pursuing various data science challenges and began to hone his data science skills.
Joining Zindi
In 2021 during his studies at the academy, he was introduced to Kaggle for one of his projects. Intrigued by the idea of machine learning competitions, Daniel wondered if there were other data science platforms out there. A quick search led him to Zindi and he joined the community.
“Zindi has helped me build confidence in my ability to understand and tackle various problems using data. This is the result of Zindi having various different competition formats and outputs, with each one being well-detailed in regards to the problem space and the desired value to be extracted,” said Daniel, in a recent interview.
Today, he ranks #2 in South Africa and #19 overall on Zindi’s online leaderboard, which ranks its community of 70,000+ data science and AI practitioners from around the world on the basis of their performance in solving real-world problems. One of many real world challenges Daniel has solved, he recently helped the Malawi public health to improve their system using large language models (LLMs).
Perseverance pays off
One of the biggest hurdles Daniel faced was the lack of a university degree, a common requirement for a data science job role. As it was just one of many requirements needed, Daniel focused on learning more, pushing himself to gain more skills through ZIndi challenges to fit these roles.
“Over time, this process transformed into something I felt proud to call experience, and I could more confidently tick those requirements boxes. Tackling challenges on Zindi came to be a great tool for this,” Daniel says.
Pathway to success
Being ranked in the top 10 computer vision specialists on Zindi, Zindi first put Daniel forward for a three month contract with a health tech start-up company that was struggling with their computer vision models. Daniel could confidently apply for this role because of his learnings from tackling various computer vision competitions on Zindi. He delivered immediate value and solved the problem. Following this success, Zindi recently helped Daniel land his first official job as a data scientist at Deloitte. Quite an achievement for someone without a formal degree!
Daniel continues his career, as he stays updated with the latest developments in data science on platforms like Zindi, commiting to improving his skills, learning, and growing.
