Gbenga M. Adebisi

About Gbenga M. Adebisi

As an individual that is given to detail, I always believed that my path lay in the natural sciences. Little did I know that my encounter with Astrophysics in the year 2020, would unveil a surprising love for data. It was an unexpected twist that ignited an insatiable curiosity within me. I came to this realization after I worked in the Astrophysics lab of Western Illinois University on the GAIA survey, which contained over a billion records. We were searching for THOR counterpart of Stars with surface temperatures between - that were not more than 100 kiloparsec from the earth. Motivated by this realization, I proceeded to become a Data Scientist. This decision made me enroll in a 10-month Data Science Bootcamp with Tripleten. During my data science studies, I developed and implemented predictive models that increased the accuracy of identifying new oil well locations by 15% and enhanced gold recovery processes by improving yield by 10%. My analysis of film reviews used natural language processing techniques to improve sentiment analysis accuracy by 25%, and my work with computer vision led to a 30% reduction in errors when verifying ages. In a culminating project, I built a machine learning model prototype that streamlined predictive analysis for a retail client, boosting their targeted marketing campaigns\' effectiveness by 40%. With an unwavering commitment to innovation, collaboration, and excellence, I am on the lookout for opportunities to bring my analytical acumen and technical prowess to a forward-thinking organization. Please feel free to connect with me here on LinkedIn or via email at e••••••••@gmail.com. If you happen to know of any data science, or data analyst positions that align with my interests and skills, I would greatly appreciate your recommendations. My Data Science projects can be found here: https://github.com/Mirac20

Experience

1. Data Scientist

   SMBC Group

   Feb 2023 — Present · JE

   Developed and implemented machine learning models to enhance credit risk assessment, resulting in a 15% reduction in default rates.• Utilized Python and PySpark for data preprocessing and analysis, handling large-scale financial datasets with over 10 million records.• Conducted exploratory data analysis (EDA) and identified key patterns, contributing to a 20% improvement in fraud detection capabilities.• Collaborated with cross-functional teams to translate business requirements into predictive models, aligning data science initiatives with strategic goals.• Implemented A/B testing methodologies, leading to the optimization of customer segmentation strategies and a 10% increase in marketing campaign effectiveness.• Leveraged Natural Language Processing (NLP) techniques to analyze customer feedback and sentiment, providing valuable insights for product improvement.• Deployed machine learning models in production environments using Docker and Kubernetes, ensuring scalability and real-time decision-making capabilities.• Conducted regular training sessions for non-technical stakeholders on interpreting and leveraging data-driven insights for strategic decision-making.• Enhanced data privacy compliance measures, ensuring alignment with regulatory standards and reducing data breach risks by 15%.• Prepared comprehensive reports and dashboards using PowerBI, summarizing key performance indicators and actionable insights for executive decision-making.

Education

• TripleTen

  Certificate, Data Science

  2022 — 2023

• Western Illinois University

  Masters, Engineering Physics/Applied Physics

  2019 — 2021

• Obafemi Awolowo University

  Bachelor's, Physics

  2008 — 2013