Rabiu

● Conducted in depth marketing data analysis using data sampling, regression, hypothesis testing to determine reason for increase in MRI and IPTs conducted by 17 of PROCO’s Clinics
● Integrated data from Salesforce to Power Bi to create comprehensive reports and dashboards to communicate marketing performance metrics to stakeholders ultimately improving data-driven decision making by 15%
● Utilized software tools like Python for regression analysis, predictive modelling to optimize marketing strategies which led to increasing return on return on investment by 35 %
● Conducted A/B testing to evaluate the effectiveness of 30+ campaigns and recommend improvements to the marketing department

Conducted in depth marketing data analysis using data sampling, regression, hypothesis testing to determine reason for increase in MRI and IPTs conducted by 17 of PROCO’s Clinics
Integrated data from Salesforce to Power Bi to create comprehensive reports and dashboards to communicate marketing performance metrics to stakeholders ultimately improving data-driven decision making by 15%
Utilized software tools like Python for regression analysis, predictive modelling to optimize marketing strategies which led to increasing return on return on investment by 35 %
Conducted A/B testing to evaluate the effectiveness of 30+ campaigns and recommend improvements to the marketing department

Analyzed data with SQL to filter entries in dataset showing yearly trends from pre COVID and post COVID time periods to identify revenue changes between both years
Created graphs using ggplot2 in R and Tableau to present the results of monthly traffic for Lakeshore, Oneida Lake, Salmon River and Tug hill whilst identifying the months with the highest and lowest lodging rate
Constructed charts and interactive dashboards using AWS Quicksight to display simplistically the highest revenue for each month and presented to Stakeholders on Power Point
Interpreted data using Microsoft excel to communicate the reason for variances in the length of stay for customers in each region

Collected, cleaned, and analyzed data from the Office of International Students using SQL and Cloud DataPrep to predict the effect of COVID on international students’ admissions application
Designed surveys and opinion polls to collect relevant data for proposing alternative ways to support study abroad students with transitioning post COVID
Used Google analytics API to automatically collect and analyze data to provide insights for debugging system integrations, improving operating efficiency by 15%
Prepared and Recommended data driven solutions to management for requesting an increase in the departments yearly budget leading to a 24% budget increase