Qudirah Alimi

Qudirah Alimi • Machine Learning Engineer Abuja, Nigeria • --• https://www.linkedin.com/in/qudirah-alimi/ • https://github.com/Qudirah SKILLS  Programming Language: Python, PostgreSQL  Data Manipulation and EDA: Pandas, Numpy, Matplotlib, Seaborn  ML / AI F r a m e w o r k s : Scikit-Learn, TensorFlow  Advanced ML Techniques: Feature Engineering, Pipeline Development, Regression Analysis, Natural Language Processing (NLP), NLTK, Hyperparameter Tuning, Supervised Machine Learning Techniques, Unsupervised Machine Learning Technique, Recommendation Engines  Business Intelligence Tools: Tableau, Plotly, Power BI, Excel (VLOOKUP, Pivot Tables, Microsoft Office), Tableau  Cloud/MLOPS: AWS, Docker, Flask, FastAPI, Rancher, MLFlow, Streamlit  Version Control: GitHub, Git, GitLab EXPERIENCE Arebak, Remote, USA • Machine Learning Engineer (07/2023) - Present  Developed and deployed a content-based machine learning recommendation system with 80% accuracy, processing over 70,000 grant records using Python and containerized AWS infrastructure for scalable production deployment  Integrated and fine-tuned GPT-based LLM to power a 95% accuracy grant match rating system, streamlining decision-making, cutting grant evaluation time by over 85%, and eliminating the need for costly human consultants  Pioneered a credit risk model using Python, Pandas, and XGBoost to identify loan defaulters; model achieved 74.6% accuracy and 81% recall, deployed with Docker and Rancher  Engineered a multifactor regression model for predictive agriculture in Kansas, resulting in a 92% R-squared value and a 15% error rate in loss ratio estimation  Forged relationships with cross-functional stakeholders via weekly report and dashboard presentations, resulting in zero major miscommunications on specifications of credit risk model and a 99.9% incident-free deployment rate Fezzant, Remote, London • Junior Data Analyst (04/2022) - (06/2023)  Performed EDA on form and social media data using Python (Pandas, Matplotlib, Seaborn) to derive customer segments, enabling tailored content strategy and increasing engagement by 60%  Developed a pipeline for data scraping and cleaning using Python and Scrapy, cutting data collection and cleaning time by 80% CONTRIBUTIONS NetworkX • v2.8.8 • v3.0 • v3.1  Managed 30+ pull requests for open-source library improvements, personally addressing minor updates and adding missing asserts, ensuring project stability and receiving positive feedback from core maintainers.  Expanded test coverage, achieving 100% coverage for key functions and reducing potential bugs SPEAKING ENGAGEMENTS Build with AI - Google Developer Student Club, Ilorin • LinkedIn • Project Link Workshop: “A Movie Recommendation System in 30 Minutes”  Orchestrated a session that guided 40+ participants through constructing a movie recommender with Python and collaborative filtering, receiving overwhelmingly positive feedback and inspiring future participation Women Techmakers Ilorin • LinkedIn Talk: “From Numbers to Know-How: How Machines Learn”  Explained core machine learning concepts to 30+ secondary school students and tech enthusiasts, bridging technical ideas with real-world impact DevFest Ilorin 2024 • LinkedIn Talk: “The Current State of AI”  Presented comprehensive findings at DevFest Ilorin 2024, detailing the limitations of current AI systems in replicating human-like general intelligence, sparking productive discussions with 50+ attendees EDUCATION University of Ilorin, Kwara, Nigeria • BSC Computer Science CERTIFICATIONS Introduction to Programming using Python Introduction to Data Science using Python Unsupervised Learning, Recommenders, Reinforcement Learning Supervised Machine Learning: Regression and Classification Graduation Year (10/2022)