Samuel Konzi

• Spearheaded the validation and reconciliation of data from multiple sources and ensured data quality and optimizing it for the flight emissions calculation API. • Developed unit tests using JUnit and MockK to validate the logic and functionality of a Kotlin-based backend, increasing code coverage by 15% and improving system reliability. • Designed and built a research database for the Power-to-Liquid (PtL) fuels project in collaboration with Solarbelt, improving data retrieval.

• Analysed datasets using Python and SQL, delivering key insights and promoting data integrity and data-driven decision making. • Revamped Metabase dashboards, enhancing visualization of business metrics and reducing reporting time by 30%, enabling faster and more informed decision-making.

• Identified irregularities and worked with Data team to rectify, ensuring quality of data streamed to company warehouse. • Performed user segmentation analysis and identified opportunity to increase campaign click rates and consequent in revenue. • Prediction of user patterns using Deep learning. • Cleaning multiple datasets for consumption by stakeholders. Technologies: • Amazon S3 • Bigquery • Python ( Pandas, Numpy , Matplotlib, Scikitlearn ,Keras) • SQL • Keras