Position: Data Analyst, Business Analyst, Analyst
Category: Data Analyst
English level: fluent
Years of experience: 6


Data Analyst, Vodafone, Ghana.
Established a growth forecasting model using Python (ARIMA) to support the FP&A team to predict revenues and promote accountability and transparency. This contributed to 5% overall revenue growth in 1 month.
Constructed 8 Tableau Dashboards with interactive views, trends, and drill-downs along with user-level security to promote transparency for leadership and 5 business teams.
Executed the cleaning of 3 million+ records in an SQL database and developed a fraud detection model to generate actionable insights for Vodafone Cash using Python. This cut monthly expenditure by 30%, resulting in $62,500+ savings monthly.
Defined and implemented the data strategy, analysis, and reporting on 3 customer growth KPIs for product and marketing teams and automated regular reports using Oracle Analytics and Tableau. This saved up to 5 man hours weekly.
Slashed churn rate by ~10% by conducting data mining, segmentation, modeling, and statistical analysis to assess customer journey on 30,000+ users and deliver data-based recommendations to sales and marketing teams.


Business Intelligence Analyst, INFUSEmedia, Boston (Remote).
Developed 5+ Visualforce pages using Apex for proprietary Salesforce applications to track the flow of business. This provided real-time data to streamline business decisions for senior management.
Collaborated with 4 cross-functional teams to perform A/B testing on 2 cold-calling techniques to simplify marketing efforts. This resulted in a more effective Lead Generation system that contributed to revenue growth.
Designed a scala and spark-based configurable framework to connect to MySQL and load in Big Query to reduce data loading time by ~10 seconds and also improve scalability.
Promoted transparency and accountability on 3 business KPIs among internal business teams and 2000+ clients by collaborating with the team to establish real-time reporting using SQL and PowerBI dashboards.
Advised mid-level management to adopt a data verification process to optimize data quality and demand generation efforts for clients. This boosted sales by ~15% in the next quarter.
Managed Enterprise analysis - planning and scoping several inter-related initiatives and supporting senior-level business stakeholders to make informed decisions about which initiatives to tackle and how to go about it.