👋 Hello world! I am a passionate Machine Learning Engineer, Data Analyst, and Data Scientist with a keen interest in turning data into actionable insights and scalable solutions. I enjoy solving complex problems and building data-driven applications that impact businesses and end-users.
- LinkedIn: [https://www.linkedin.com/in/oguguamakwa-obidike]
- Email: [[email protected]]
- Languages: Python, R, SQL
- Libraries & Frameworks: Scikit-learn, Pandas, NumPy
- Matplotlib, Plotly
- Clustering, Forecasting, Predictive Modeling, Multivariate Regression
- NLP, LLMs, Churn Prediction, Recommendation Systems
- Automatic Speech Recognition, Text Mining, Bayesian Inference
- Hyper-Parameter Tuning, Binary Cross-Entropy
- EDA, Data Wrangling, Statistical Testing
- ETL/Data Pipelines, A/B Testing, Statistical Analysis, Trend Analysis
- Docker, Flask, Agile methodologies (Kanban, Scrum)
- Microservices, REST APIs
Role: Data Scientist/ AI Developer
Technologies: Python, OpenAI API, NLP
- Developed a Python-based chatbot framework leveraging OpenAI's GPT-3.5 Turbo API.
- Designed a modular, reusable
Chatbotclass to support customizable system prompts and dynamic conversational styles. - Implemented error-handling mechanisms to manage API rate limits and ensure reliability.
Role: Machine Learning Engineer/ Data Analst
Technologies: Python, Flask, MongoDB, Scikit-learn, Plotly
- Built a MongoDB database and a custom class to generate and manage unique monster characters.
- Integrated the database with a Flask app, enabling dynamic visualizations and interactions.
- Used a Random Forest Classifier to achieve 99.5% predictive accuracy on targeted monster attributes.
Role: Data Analyst
Technologies: SQL, Python, SQLite3
- Conducted advanced SQL queries to uncover insights into the Northwind database.
- Automated query execution using SQLite3 and Python to streamline workflows.
- Enhanced reporting and visualization for supplier, product, and employee analysis.
- Artificial Intelligence: Applying deep learning RL and AI to solve real-world problems.
- Data Engineering: Optimizing data pipelines and working with large-scale datasets.
- Natural Language Processing: Developing systems for understanding and generating human language.
- Algorithmic Thinking: Continuously improving my problem-solving techniques and understanding of advanced algorithms.
2022 - Present
- Achieved 98.1% accuracy in predictive models using RandomForestClassifier and advanced hyperparameter optimization.
- Conducted extensive EDA on datasets, uncovering key insights and trends for multiple Data scraping projects.
- Developed a local chatbot using short-term memory models to enhance user interaction.
2020 - 2022
- Improved operational efficiency by managing shipment data and identifying delivery bottlenecks.
- Reduced stock discrepancies by 15% through inventory monitoring and reporting.
- Conducted trend analysis of delivery schedules to improve customer fulfillment.
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BloomTech
Graduate of the Data Science/Machine Learning Program -
Rider University
General Biology
Feel free to connect with me for collaborations, discussions, or just to talk about data and tech! 😊