Position: Data Analyst
Category: Data Analyst
English level: fluent
Years of experience: 1.5

Maximizing the power of data has always been fun for me and brings a sense of fulfilment — the challenge of using numbers to tell a story and convey an idea.
One remarkable period my resilience was tested, was getting Executives onboard for the data strategy project. It is a known fact that Executives play a crucial role in the crafting and realizing an organization’s data strategy and when Executives are yet to see the need for a data product, then the question of “How do we get management to agree that our organization needs to pivot into the adoption of this BI tool?”. 
I worked with a Data Scientist who at the time helped build models which were impactful for detection and descriptive analysis, however stakeholders had not seen a reason to adopt the technologies necessary to deploy such a product. 
So, I went ahead and scheduled a meeting with all necessary stakeholders, I went ahead and translated the insights into a dashboard using the free tool of Google Data Studio showing them the advantages of adoption. Some of this would be showing the Fraud team how the Machine Learning Model could help flag suspicious customers, the Client Experience Managers how the RFM model could help with the classification of customers and study behavioral patterns and reduce the customer churn rate from 40% to 15%. 
Although this took about 8 weeks of sharing actionable insights with stakeholders and strategic sessions, the organization eventually made the decision on the adoption of the BI solution.
I have worked on a number of projects which was beyond the tools but also about understanding the data and extracting important information. These projects covered the different dimensions of  analytics: Descriptive Analytics, Diagnostic Analytics, Predictive Analytics and Prescriptive Analytics. Some of the projects have conducted used data to improve revenue, launching a data-driven product, improve existing product offering, correlation analysis, market research.
For these projects I leveraged SQL, Python, PowerBi and code scheduler (for the automation and code scheduling).