Areas of Expertise
- Data Mining and Analytics
- Artificial Intelligence/Machine Learning
- Information Systems Management
- Building recommender systems
- Building churn prediction models
- Improving decision making using available business, product and customer data
The Top Three Things I Would Like to Learn or Experience During my Mentorship
- Gain practical experience using big data to work on a machine learning model (e.g recommender system/churn prediction) while learning about the corporate culture at a large global tech company
- Advance my skills as a technical trainer given that I am currently being onboarded as a new LinkedIn Learning Instructor
- Meet and network with leading data science practitioners and thought leaders in the San Francisco Bay area and gain insight into how to thrive as a C-suite leader while remaining a data specialist as well as explore collaboration opportunities
Ideal Company Type
My ideal placement would be to work on a machine learning model at a prestigious leading data-driven company. This will enable me to apply the learnings when I return to my company (a leading African tech firm) where I have faced bottle-necks when attempting to build machine learning models due to lack of technical mentorship. My desire is to be placed at a fast-paced Tech Giant which prioritises data-driven decision making as well as employee engagement and growth. Ideally I would also like to engage with the Tech Giant's leadership and so would hope for a company with approachable leaders.
- Microsoft Azure Data Scientist Associate
- Data Science Certification (WorldQuant University, December 2019)
- Data Science (IBM)
Additional Technical Skills
Python, SQL, Building Analytics Dashboards using Qlik, Building Analytics Dashboards using PowerBI
What are three adjectives that best describe you in the work place?
What impact will your mentorship have on your career and professional path?
The TechWomen mentorship will allow me to do two things. The first is to advance my technical expertise. My ideal TechWomen project would be to work hands-on on a machine learning model under an expert at a leading data-driven company. This will enable me to apply the learnings when I return to my company where I have faced bottle-necks when attempting to build machine learning models due to lack of technical mentorship. The second thing the program will assist me with is scaling up my impact and visibility as a local role model and mentor.
After participating in the TechWomen program, how will you leverage your mentorship experience to make an impact in your home country?
My immediate goal is to build a machine learning model at work, it is Zimbabwe’s leading technology company and I would be the first female to do so. Longer term I plan on expanding my mentorship work by onboarding mentors from TechWomen fellows and Silicon Valley professionals. The TechWomen website has a Fun Tech Facts section - I would also love to create a dashboard with insights about TechWomen impact. Lastly, the networking opportunities will provide a pool of like-minded professionals to learn from and look to for inspiration and support in my journey as an influencer in data science.
Years of Full-time Work Experience9
Primary Professional Focus
- IT systems and/or data analysis
- Scientist and researcher
- Technical training
Current/Most Recent Job
- Title and Company: Data Scientist, Cassava Smartech
- Direct Reports: 2
- Type: Full-time
- Location: Harare, Zimbabwe
- Dates: February 1, 2018 –
Automate previously manual reporting processes by deploying analytics dashboards to track key business metrics; Identify and create new business metrics; provide business intelligence insights for various business units; Conduct data classification exercises; Conduct analytics deep dives for several business units; Train end users on analytics dashboard creation and use; Work on machine learning models to predict product adoption; Engage executives and product teams to understand their business needs and provide advanced analytics solutions.
- Title and Company: Finance and System Administrator, Export Trading Group
- Type: Full-time
- Location: Harare, Zimbabwe
- Dates: December 10, 2012 – January 31, 2018
Ran the out-grower department's project administration, reporting, monitoring and evaluation and data analysis. Also responsible for project planning, budgeting and grant management; Designed, maintained and analysed the smallholder farmers databases and field performance reports; Managed donor funds and was the main liaison between the organisation and donor administration.
Highest Level of Education CompletedBachelor's
- Institution: National University of Science and Technology
- Degree Awarded: Bachelor's
- Major: Applied Mathematics
- Location: Zimbabwe
- Completion Date: May 1, 2012