CV

Click here for the pdf version

OBJECTIVE STATEMENT

I specialize in advanced analytics and aim to utilize my skills in machine learning and data manipulation to contribute valuable insights and address intricate data challenges within a collaborative team environment.

EDUCATION

Bowling Green State University. Bowling Green, USA. May 2027.

• Major: Data Science, Doctor of Philosophy.
• Relevant Coursework: Big Data Analytics, Data Science Ethics, Statistical Learning

Bowling Green State University. Bowling Green, USA. May 2024.

• Major: Data Science, Masters.
• Relevant Coursework: Machine Learning, Data Science Programming, Database Management System, Probability and Statistics.

African Institute for Mathematical Sciences. Dakar, Senegal, July 2022.

• Major in Big Data and minor Statistics, Masters.
• Relevant Coursework: Machine Learning, Deep Learning, Statistics and Probability, Data Mining and Big Data Analytics.

University for Development Studies. Navrongo, Ghana, June 2019.

• Major: Finance and minor: Mathematics, Bachelors.
• Relevant Coursework: Corporate Finance, Calculus, Numerical Methods, Operations Research.

PROFESSIONAL EXPERIENCE

Graduate Assistant, Student Success Analytics and Technologies. Bowling Green, US. Aug 2022 – Present

• Collaborate with cross-functional teams to understand data analysis needs and deliver actionable insight.
• Utilize advanced PowerBI functionalities to visualize and interpret complex data sets for academic performance metrics.
• Implement Python scripts to clean, transform, and prepare large volumes of educational data for analysis.
• Conduct rigorous statistical analyses to identify trends and patterns in student success data.
• Design and maintain cloud databases for efficient data storage and quick retrieval for analysis purposes.
• Employ machine learning algorithms to build and refine predictive models related to student outcomes.
• Develop and test hypotheses related to student engagement, performance, and retention using quantitative methods.
• Present findings to faculty and administration to inform data-driven decision-making processes.
• Maintain strict data privacy standards and ethical research practices when handling sensitive student information.

Data Science Fellow, ICRISAT/CLU. Tucson (Remote), USA. March 2022 – August 2022

• Conducted in-depth review of 10+ crop research papers in Senegal, extracting essential variables for analysis.
• Enhanced and maintained scripts for parameter extraction in crop simulation, supporting the DSSAT project.
• Improved performance of existing crop parameter extraction scripts, optimizing data processing.
• Delivered weekly project progress presentations to stakeholders.
• Utilized OpenAI’s GPT-3 to conduct prompt analyses for crop sentiment analysis.
• Implemented cosine similarity analyses on extensive texts to identify keywords in crop research.
• Contributed to a project focused on belief extraction from large textual datasets.
• Submitted a pull request for the HABITUS project on GitHub, contributing to open-source development.

Data Scientist Jr, Obertys Technologies. Dakar, Senegal. June 2022 – March 2022

• Developed Credit Scoring Model, improving loan approval accuracy by 20%.
• Analyzed data from 15 financial institutions, leading to $55k in potential savings.
• Created 30+ novel features for enhanced model performance.
• Led model experimentation, achieving a 15% accuracy boost and 10% reduction in false positives.
• Innovated queuing management algorithm, reducing processing time by 25%.
• Designed an automated data pipeline, cutting preprocessing time by 30%.
• Implemented data security measures for GDPR compliance.
• Collaborated cross-functionally to align projects with business goals.
• Mentored junior team members for improved productivity.
• Consistently met project deadlines.
• Maintained the company projects GitHub resources.

Data Scientist Jr, Baamtu Technologies. Dakar, Senegal. Feb 2021 – June 2022

• Spearheaded end-to-end computer vision project, encompassing data collection (drones and satellite imagery), annotation using LabelStudio, and extensive image preprocessing.
• Orchestrated a project pipeline with custom preprocessing functions and utilized transfer learning for feature extraction and model training.
• Achieved an impressive 89% Intersection over Union (IoU) score through rigorous model experimentation.
• Engineered a user-friendly presentation dashboard with Streamlit for seamless communication with the team and supervisors.
• Actively participated in weekly project meetings, ensuring ongoing alignment and consistent progress update.

DATA SCIENCE PROJECTS

Fake News Detection with Fine-Tuned Transformers: Python, PyTorch, Jupyter Notebook.

• Adapted a state-of-the-art transformer-based neural network for fake news classification through advanced fine-tuning techniques.
• Conducted numerous experiments to optimize the model’s hyperparameters, resulting in a highly accurate system capable of discerning authentic news from fraudulent content.

Potato Disease Identification via Transfer Learning on CNN: Python, TensorFlow, Jupyter Notebook.

• Engineered a transfer learning approach utilizing a pre-trained Convolutional Neural Network to classify various potato diseases.
• Achieved a high degree of model precision with a 96% classification accuracy by iteratively fine-tuning and validating the CNN on a dataset representing 10 distinct disease categories.

Geospatial Building Segmentation for Real Estate with U-Net: Python, PyTorch, LabelStudio.

• Developed a U-Net deep learning model for efficient geospatial segmentation of rental properties in Senegal using satellite imagery.
• Enhanced building localization in urban imagery for real estate assessment using advanced image segmentation techniques.

SKILLS & TOOLS

• Programming Skills: Python (PyTorch, TensorFlow), R, C++, JavaScript
• AI & ML Concepts: Computer Vision, NLP, Predictive Modeling, Graph ML.
• Data Management & Analytics: SQL, NoSQL (MongoDB)
• Tools: Jupyter, Visual Studio, Git, PowerBI.
• People Skills: Team Player, Emotional Intelligence, Sociable
• Communication: Written and Oral

RESEARCH EXPERIENCE

• Annotating and Training for Population Subjective Views. Maria Alexeeva; Caroline Hyland; Keith Alcock; Allegra A. Beal Cohen; Hubert Kanyamahanga; Isaac Kobby Anni; and Mihai Surdeanu. In 13th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, 2023. link