Enoch Bayode

IIori Streamline Ltd • Remote, London, UK

Built and deployed real-time predictive monitoring workflows and analytics engines for production environments. Engineered solutions using regression, variance analysis, and control-limit modeling for trend prediction and forecasting. Integrated live sensor data with baseline models and database storage into unified pipelines for automated alerting and data traceability. • Built and deployed a real-time predictive monitoring workflow that automated deviation detection and early-warning alerts, reducing operational monitoring time by 80% and improving decision response speed. • Engineered a rolling-window analytics engine using regression, variance analysis, and control-limit modeling, enabling accurate trend prediction and time-to-breach forecasting across multiple process parameters. • Integrated live sensor data, baseline models, and Supabase storage into a unified n8n pipeline, delivering reliable batch processing, automated alerting, and end-to-end data traceability for production environments.

Cratadel • Nigeria

Lead and manage a tech and entrepreneurship community of 120+ members focused on empowering Africans to create innovative solutions tailored to the continent's unique challenges. Design and deliver hands-on programs including webinars, workshops, and mentorship sessions. Host ThinkAfrica Podcast discussing innovation, technology, and entrepreneurship in Africa. • Currently lead and manage a tech and entrepreneurship community of 120+ members, focused on empowering Africans to create innovative solutions tailored to the continent's unique challenges. • Designed and delivered 25+ hands-on programs (webinars, workshops, mentorship sessions), strengthening practical skills in Tech and entrepreneur. • Host of the ThinkAfrica Podcast, a platform discussing innovation, technology, and entrepreneurship in Africa, highlighting practical AI-driven/tech solutions and locally relevant use cases.

TechnicallyArt • Remote, USA

Built and deployed AI-powered chatbot for predicting oil & gas reservoir properties. Designed scalable ML pipelines on Azure Machine Learning for training, evaluating, and deploying predictive models. Integrated Azure ML, Azure Data Lake, and Azure Functions to automate data ingestion, model retraining, and real-time prediction. Implemented CI/CD workflow using Azure DevOps for reproducible experiments and smooth model updates. • Built and deployed an AI-powered chatbot that predicts oil & gas reservoir properties, enabling engineers to get instant insights and reducing manual analysis time by over 30%. • Designed scalable ML pipelines on Azure Machine Learning for training, evaluating, and deploying predictive models used in exploration workflows. • Integrated Azure ML, Azure Data Lake, and Azure Functions to automate data ingestion, model retraining, and real-time prediction across production systems. • Implemented a reliable CI/CD workflow using Azure DevOps, ensuring reproducible experiments and smooth model updates without disrupting active users with a 40% faster release cycle.

TelepracticePro • Remote, Atlanta, GA, USA

Designed and deployed multi-tenant RAG chatbot and AI assistant using OpenAI GPT-4o-mini, Pinecone, PostgreSQL, and FastAPI. Built AI-powered note-taking system using OpenAI Whisper and GPT for real-time transcription and automated medical form population. Delivered production-grade, scalable APIs combining software engineering with applied LLM capabilities for healthcare automation with HIPAA compliance. • Designed and deployed a multi-tenant RAG chatbot and AI assistant using OpenAI GPT-4o-mini, Pinecone, PostgreSQL, and FastAPI, enabling secure, context-specific responses for multiple organizations within a shared platform. • Extended the assistant to perform in-app actions, such as navigating users to service pages, tracking feedback, and managing chat history. • Built an AI-powered note-taking system using OpenAI Whisper and GPT, featuring endpoints for real-time transcription, full-session summaries, and automated population of medical forms using extracted clinical terms. • Delivered production-grade, scalable APIs using FastAPI, async Python, and GCP, combining software engineering with applied LLM capabilities to solve real-world problems in healthcare automation which are HIPAA compliance.