Data Scientist

• Apr 2021 - Present

Software Engineer Intern

• Jun 2022 - Aug 2022

Machine Learning Engineer

• Jul 2020 - Apr 2021

Functioned independently in developing machine learning and data science models responsible for capturing operational data, monitoring how the data are delivering aid and successfully enhancing performance by 25% for a relief fund. • Researched and designed computer vision models to recognize and classify entities in images which assisted in the fund’s COVID-19 relief by understanding 97% of pictures taken in conflict zones. • Applied Optical Character Recognition on textual data that successfully processed 98% of the key contents of receipts, addresses, locations etc. that helped the relief fund in financial modeling and scenario planning. • Worked closely with the Chief Technology Officer in setting up and maintaining the portal across sites, each based on its data-driven purpose for deploying these models to the cloud using Microsoft Azure and its API platforms which proved effective for operation planning.

Data Analytics Lead

• May 2020 - Apr 2021

Research and Technical Lead

• Jan 2020 - Apr 2020

• Engaged in enlightening West African students on state-of-the-art machine learning concepts and data science tools for analysis.• Involved in researching techniques on improving and ‘boosting’ model performance to a target of 90% accuracy and recall.

Data Science Intern

• Sep 2020 - Dec 2020

• Designed and developed small scale analytics deliverables related to the needs of the company and its clients as well as monitoring results for accuracy, consistency and statistical validity. • Improved the data mining process via Python, SQL and database management tools, resulting in a 50% decrease in time needed to infer insights from customer data for workplace efficiency as well as a 30% increase in usability of these techniques for non-technical users. • Refined the analysis and visualizations using Tableau and Python that comprise a core part of the company’s product architecture, achieving 20% more accurate performance than previous quarters of the company.

Data Science and Research Intern

• May 2020 - Jun 2020

• Researched and analyzed data using Python for getting new leads on possibilities of testing and launching a potential product idea for businesses and startups. • Managed the team’s database to identify useful datasets for data science projects based on needs. • Collaborated with a self-functioning and cross-functional team in developing machine learning, software engineering and data science solutions for over 10 client works across different platforms. Achieved 90% significance in relevant data science solutions.

Virtual Intern- Data Analytics

• Jan 2020 - Apr 2020

• Identified data quality issues and integrated strategies such as data wrangling and exploration using Excel, SQL and Microsoft BI in the ETL phase to mitigate these issues. • Implemented analysis and accurate machine learning models in Python and R on the resolved data that would reveal useful customer insights for optimising resource allocation for targeted marketing. This improved performance by 10% via focusing on high value customers. • Visualised and prepared results using Tableau’s interactive dashboards to highlight key findings for evaluation and convey the ideas.

STEM Tutor

• Dec 2019 - Apr 2020

• Provided quality answers in the content tool to high school and undergraduate questions in the field of Science, Technology, Engineering and Mathematics (STEM). Achieved 90% rate of correct solutions. • Worked with the review team in evaluating answers on a weekly basis and modified appropriately to facilitate the understanding of students. • Provided quality answers in the content tool to high school and undergraduate questions in the field of Science, Technology, Engineering and Mathematics (STEM). Achieved 90% rate of correct solutions. • Worked with the review team in evaluating answers on a weekly basis and modified appropriately to facilitate the understanding of students.

Member

• Mar 2019 - Jan 2020

Machine Learning Bootcamp Participant

• Jul 2019 - Jul 2019

 PROJECT: “Minimising cost and maximising profit using supervised machine learning prediction model” o Implemented machine learning algorithms using Python to choose the best departments to invest in a company working with CSV database. o Marketing department was chosen the best as a unit increase in its spend corresponded to 79 cents increase in profit using backward propagation. o I used the pandas, numpy, matplotlib, scikit-learn software packages in the algorithms and considered the Decision Tree and Random Forest techniques. o Visualised the results and led the presentation, which was chosen the best among my colleagues.