experience
FEB 2019 – DEC 2019 KUDOBUZZ/Kudobuzz.com Kudobuzz is a marketing SaaS solution that helps small and medium online merchants increase their sales using social reviews, SEO and marketplace feed submission. Customer Success Engineer. I worked with over 1000’s of ecommerce merchants to address their SEO needs and help them gain more traffic on Google by following webmaster guidelines as well as onboard them on how to curate reviews and Submit their products to multiple feeds across multiple market places. Customer Success: Upsell & Cross-sell campaigns to users. Also solving critical challenges faced by Merchants, this also involved working closely with the product team to ensure fast and efficient handling of bugs. Leadership & Teamwork: I worked closely as a team with a team of 28 spread across the African continent. Onboarding: By refining the existing help guides and also creating more to allow users to seamlessly integrate with our Apps. NodeJS Intern As a NodeJS Intern I worked under the guidance of the CTO to learn and how to refine my skills as a developer, this involved an intensive learning process that involved creating a boilerplate for building Restful APIs with NodeJS Micro services: The Codebase at Kudobuzz utilized micro services and this refined my developer experience to learn how to utilize this to the full potential Building Restful APIS: Created an express API starter boiler plate for building applications with NodeJS API documentation: I learnt how to apply and employ the different rules and techniques for API documentation.
NOV 2018 – JAN 2019 PI CONSULTING/pycs.co.ke Pi Consulting is a Fintech Company that offers a vast range of Financial products such a s loan apps and many more to seek to resolve recurrent problems that financial institutions face. DATA ANALYTICS INTERN.
2
I worked with data from over 25000 Users to Identify set patterns that borrowers have set to identify the highest probability for a user to default on a loan as well as Identifying potential good customers who are refined borrowers and how we can utilize them. Predictive analysis: Assessing client behavior and building a predictive model to show the probability of default in their loans. Research: This involved identifying new machine learning techniques that have been simplified for day to day use that we could implement in our system and also identifying new algorithms to use to better assess our users on who is more fit to acquire a higher loan Data Analysis: Working hand in hand with my colleagues we curated data from existing users and developed a test model based on the scores provided by the Credit Reference Bureau to identify the best range of customers to lend to. Python: Took up on a series of learning python to latter trickle into data analysis.
MICROSOFT4AFRIKA APPFACTORY Research Associate: I worked on a real world project combating deforestation using Sensor networks and implementing defense mechanism using Internet of Things.
Worked with Design thinking and Systems Thinking to create and provide real world solutions that are centered on the User this allows us to make long-term usability and gravitate our solutions around growth and transformative ideas.
