About

Cannel Maina is a data scientist and fintech enthusiast with a diverse skill set that includes Python, Flask, Docker, AWS, R, R-shiny, SQL, Excel, PowerBI, Tableau, Forex, blockchain, and cryptocurrency. With 1.43 years of relevant experience, she is passionate about data science and machine learning and is always eager to share her knowledge with others. Currently working as a Software Implementation Specialist at ezen partners ltd, Cannel helps companies go live with stipulated deadlines. She is conversant with real estate commercial tax systems and has experience integrating bulk SMS APIs, bank APIs, and Mpesa daraja APIs with various systems. Additionally, she helps clients maintain their books of account and has excellent presentation and storytelling abilities. In the past, Cannel worked as a freelance data analyst, where she gained experience with various data storage tools such as SQL, statistical analysis using Excel, and advanced knowledge in time series analysis. She has also modeled predictions with feature selection algorithms, regression, cluster analysis, and classification, and implemented randomized sampling techniques for optimized surveys. Cannel is proficient in developing polished visualizations to share results of data analyses using various visualization tools such as Microsoft PowerBI, Tableau, and other libraries such as matplotlibpyplot, seaborn, ggpplot2, and Tstudio packages both in R and Python. Cannel's education background includes a BSc in financial engineering from Jomo Kenyatta University of Agriculture and Technology, where she studied quantitative research analyst, predictive analytics, and risk assessment. She also holds a Kenya Certificate of Secondary Education from Murang'a High School. Cannel's tech stack includes data science, research science, SQL, integration, AWS, blockchain, Python, Docker, ML, Flask, and Seaborn. She is always looking for new challenges and opportunities to apply her skills and knowledge to help companies make data-driven decisions.