David Kadala

- |-www.linkedin.com/in/david-kadala Davd Kadala | Data Science Portfolio Gombe, Nigeria 760251 Data Scientist/ Machine Learning Engineer DAVID KADALA Skills Programming & Data Science: Python (Scikit-learn, Pandas, NumPy, Matplotlib, TensorFlow, BeautifulSoup, SQLite) Cloud & Collaboration Tools: Google Colab, Looker Studio, Git Machine Learning & AI: Model development, feature engineering, hyperparameter tuning, model evaluation Generative AI & Prompt Engineering: Optimizing workflows with AI-powered tools Data Processing & Analysis: Web scraping, exploratory data analysis (EDA), data cleaning, visualization Office & Productivity: Microsoft Word, Excel Projects LO AN PRE D IC TI ON M O D E L – Virtual Client’s Project – Nigeria ● ● ● ● ● Developed a classification machine learning model (Logistic Regression) to predict loan approval based on applicant data. Preprocessed data using pandas and NumPy, and performed feature engineering improving model accuracy. Implemented logistic regression using Scikit-learn and optimized hyperparameters for better performance. Visualized insights using Matplotlib and Seaborn to understand key factors affecting loan acceptance. Presented a deployable output to DevOps team using joblib. GO OG LE PL A YS T ORE AN AL Y SI S FO R AP P DE VE L O PM E N T – Virtual Client’s Project – Nigeria, ● ● ● February, 2025 February, 2025 Analyzed Google PlayStore data, uncovering trends in app categories, pricing and rating, guiding product development decisions. Cleaned and processed 10K+ rows of data, improving data quality for accurate insights. Provided technical insights on how the client can fully utilize their data by introducing different technologies Visualized findings using Matplotlib and Seaborn, presenting actionable recommendations to stakeholders. Work Experience D AT A SC IE N TI S T/M AC H I NE LE ARN ING E NG INE E R – Outsource Global – Abuja, Nigeria ● ● ● ● Performed web scraping using Python libraries (BeautifulSoup, Scrapy) to extract and process large datasets, improving data collection efficiency by 40%. Conducted exploratory data analysis (EDA) using Pandas, NumPy, and Matplotlib, uncovering key trends that enhanced business decision-making. Built and optimized machine learning models for predictive analytics, achieving up to 20% increase in prediction accuracy through feature engineering and hyperparameter tuning. Collaborated with teammates on major projects, performing peer reviews to optimize code performance and scalability. HI G H SC H OO L C HE M I S T RY TE A C HE R – ECWA Good News Schools – Gombe, Nigeria ● ● ● October 2024 - Present June 2019 - September 2024 Analyzed student performance to identify trends, improving learning outcomes by up to 15% through data-driven strategies. Applied problem-solving and analytical thinking to break down complex concepts, skills transferable to data science model development and interpretation. Utilized Artificial Intelligence for automated workflows leading to more focus on major task and student engagement. Education B AC HE LO R OF S CIE N C E E D UC TI ON IN C HE M I S TR Y – University of Jos – Jos, Nigeria Majors: Educational Technology, Chemistry July 2017