Hi Philip Nduka here,

As a Data Scientist and Machine Learning Engineer, I am driven by the mission to transform complex data into actionable, measurable insights. With a solid foundation from my MSc in Computer Science with Data Science and BSc in Mathematics, I specialize in designing, deploying, and optimizing advanced data-driven systems.

My expertise is centered on building and scaling intelligent AI and ML solutions that tackle real-world challenges. From crafting sophisticated predictive models and efficient ETL pipelines to implementing robust AI systems, I am adept at merging statistical computing, database management, and web development to deliver powerful solutions.

Key Expertise

My technical proficiency spans multiple domains, with a focus on delivering high-impact results:

• Machine Learning & AI: I have a proven track record in developing and fine-tuning Large Language Models (LLMs), including BERT, GPT-2, and Electra, for tasks like fake review detection and conversational AI. My work extends to deep learning for image classification and applying sophisticated neural network architectures to solve diverse challenges.

• Data Engineering: I excel at building and optimizing intelligent data pipelines for unstructured content, integrating ML workflows, and deploying enterprise-scale AI applications. My skills include using PySpark, vector databases like Qdrant and FAISS, and implementing Retrieval-Augmented Generation (RAG) systems.

• System Deployment & Automation: I am experienced in deploying production-ready machine learning systems using tools like Docker and Kubernetes. I also have extensive experience with web automation tools such as Selenium and Playwright, ensuring seamless integration and efficient workflows.

My work is characterized by a commitment to technical excellence and a passion for innovation. I am dedicated to pushing the boundaries of what AI and data science can achieve to deliver transformative solutions.