Walu Maclean Kaira

At Ampere Analysis, I collect and transform data from subscription video-on-demand platforms, social media, data banks, APIs, and websites to support market analysis and reporting.

I've built prediction tools with machine learning, data-quality functions, and tested complex query builders with pytest. I use Python, Playwright, PostgreSQL, Power Query, Power Automate, Docker, AWS RDS, Qlik, and Power BI to extract, manage, visualize, and validate data.

As a consultant data analyst at Namene Solar, I wrote Python code to track carbon-emissions reductions and managed daily and monthly ETL pipelines for sales and client data on EC2.

My chemical engineering and research background includes laboratory studies, techno-economic feasibility work, and contributions to five published articles on wastewater treatment, anaerobic digestion, and resource recovery.