I am a machine learning engineer/researcher interested in applying artificial intelligence to sustainable projects. Previously, I have worked in fintech as well as in the energy space and hope to continue working on projects that directly impacts the needs of the average human. I am skilled in various programming languages, building ML models from scratch and with existing libraries, MLOps and foundational software engineering
Get In TouchConcentration: Applied Machine Learning
Python, Java, C/C++, SQL
NumPy, Pandas, Matplotlib, Seaborn, Scipy, StatsModel, Tableau, Metabase, SQL, A/B Testing, MS EXCEL, Google Data Studio
Sci-Kit Learn, Pytorch, Tensorflow, Tensorflow Data Validation, Hugging face, Flask
PostgreSQL, MySQL, AWS, Git, Docker, Linux, DevOps
• Working with Dr. Nathan Williams on electrification problems in Sub-Saharan Africa. Current Project in Nigeria, to estimate the latent demand for electricity in the region
• Came up with proprietary ML algorithms for flow detection on home heaters with potential to save the company over 40% installation cost on every HotBot installed in the homes of customers
• Worked with the operations team to provide insight from the data produced by all departments and foster growth in the company
• Maintained and updated back-end queries to constantly meet business needs in terms of the data pulled out
• Created over 90% of the data engineering processes as well as the various reporting and visualizations used by the various departments in the daily running of the company
• Utilized Machine learning to build a yield prediction algorithm for mini-grid connections in rural Africa
• Evaluated the possibility of data-backed refinancing for mini-grid connections by combining clustering, and classification algorithms
• Worked extensively with geospatial data to understand how development affects electricity access and consumption in rural villages.
• Conducted statistical and data analysis with captured data and provide business intelligence to aid decision processes for the Operations, Marketing and Tech departments.
• Achieved 2,650% increase in active savers within 3-months from launch by pioneering data-driven initiatives on customer acquisition and retention.
• Built tools from ground-up that provided 100% visibility into KPIs across the entire company.
• Deployed GPS trackers and Maintenance Information Systems on over 200 oilfield assets (covering about 60% of the project, within a month) for better asset and maintenance management as part of the Global Traceability Project
• Maintained and certified pressure control equipment such as treating lines and valves to provide up to 99.99% availability on the field
• Conducted routine maintenance on oilfield equipment, i.e., pumps, engines, mixers, etc. that ensured downtime was near 0 hours.
