With a background in statistics, I boast of vast data science, data engineering and stastistics knowledge. Not only do I excel in data collection, data cleaning & preparation, exploration data analysis (EDA), visualizations, modelling, prediction and forecasting but also great SQL and web scraping skills. I am a self-taught DevOps engineer, something I really like doing. I am love solving problems analytically. In summary, my skills include but are not limited to: - data engineering, data science, analytics, visualizations, prediction, machine learning and statistics - DevOps [version control, CI/CD, orchestration and containerization, Infrastructure as Code (IaC), Monitoring and Logging, Cloud Platforms, & Configuration management] - natural language processing, AI & prompt engineering - technical writing, report writing, medical statistics, biostatistics, proofreading and editing Statistical tools: R, Python, Tableau, Power BI, Matlab, Eviews, SPSS, flexMIRT, JMP, SAS, STATA, Minitab, Rapid Miner, SQL DevOps: Git, Jenkins, Travis CI, AWS & Azure, Kubernetes, Terraform, Ansible, Linux, Docker, Prometheus, Grafana & ELK Stack Programming Languages: Go, Python