Reviews

Victory and I crossed paths in 2021 when he came on board as the lead facilitator of the data analysis track of our DigiGirls program.
Victory’s exceptionalism was evident from the very beginning. He was responsible for creating the curriculum for the data analysis track which was approved to be used for training by the UK government. He also delivered live and recorded classes to the cohort which had over 1000 beneficiaries.
Victory was able to explain technical concepts and software like Structured Query Language (SQL) for querying databases and Microsoft excel for data analysis to the beneficiaries using simple and clear examples and methods. The cohort recorded a huge success with about 25% of beneficiaries landing jobs in the data analysis space within 3 months of graduation.

There were a lot of positive reviews from the beneficiaries and the UK government and Victory was invited to facilitate the data analysis track for the second cohort.
In the early stages of the second cohort, Victory’s constant drive for improvement was obvious. He immediately made strategic adjustments to the curriculum adding modules for data visualisation to better help the beneficiaries meet the present demands of the data analysis world.
This improved curriculum was approved and adopted to teach about 5000 beneficiaries in the data analysis path. Over a hundred of those beneficiaries have gone on to join leading banking, Fintech and other technological firms across Africa.

Victory has been pivotal to us here at Cybersafe and I'm sure he will be an asset to any organisation in the world.

Victory first joined the Utiva team as a student in the data accelerator program during the 2020 pandemic. On my first call with Victory, it was evident that he had a passion for the technological industry. I was sure that with a little guidance, he would transform the data science scene.

Well, my intuitions were right! Just three months after beginning training, Victory joined Darlytics as a data analysis intern where he started using his newly learned skills to query and transform data. After this, he joined one of Nigeria's leading fintech companies, Carbon as a business intelligence analyst. At Carbon, he was in a team of four people on three different continents. This role really amplified not only his technical skills and prowess but also his teamwork and interpersonal relationship in a remote working world.

Victory’s success in very little time caught the attention of the Utiva team and he was invited to facilitate the data accelerator cohort at Utiva. He effectively managed a cohort of over 500 beneficiaries and his students left very good remarks about his ability to communicate new and complex concepts to them. Over half of his students have gone on to make giant strides in the data analysis sector.

Victory’s story is nothing less than an exceptional talent with a very bright and promising future. I am immensely proud of how far he has come. His tenacity and drive for knowledge over the years have been outstanding. It is because of these that I can boldly say Victory is definetely a great advantage to any company he works with in the future.

In July, 2022, the analytics team at Blue Motor Finance began searching for a data scientist who could come on board to build a machine learning model for the collections team. Victory’s profile stood out because of his previous experience in analysing loan data and creating algorithms with the technologies similar to the ones used at Blue.

Victory showed a good understanding of the steps needed to build an efficient data science model. He was diligent and patient to understand how the business works and what the task at hand was before he began to query the database using Blue Motor’s Microsoft Sequel server. He was able to gain quick understanding of the database and showed great prowess in his Structured Query Language (SQL) skill by creating, transforming and modifying fields when necessary. His SQL codes were reviewed and he was praised for clarity and consistency when creating the output data needed.

Victory then moved on to input the data into the python environment where he built the model with advanced python libraries and functions. The model had an accuracy of over 90% and thus, the collections team have since been able to predict if a customer will fail on an expected payment a week before the expected payment date.

This model was very important to us at Blue and Victory knew just what to do to get it up and running. I am positive that Victory's work ethic will be a great addition to any team he joins in the future.