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

As a Data Analyst, I developed monthly sales leads which led to a 10% increase in product sales strike rate.

As a Data Analyst, I was part of the team that created a Customer segmentation model and created personas that lead to a more personalized and improved sales process for the bank.

As a relationship manager, introduced various programs and initiatives to improve branch profitability, moving from loss-making to profit-making and
achieving > 50% of the PBT target for the first time in 5 years.

As a relationship manager, I solely fulfilled 90% of branch loans and new customer acquisition targets.

As a relationship manager, I increased revenue and profitability by growing wallet share, sourcing and delivering business credit solutions, cross-selling
bank products, achieving high levels of customer satisfaction.
Created sales leads using complex SQL queries and KNIME workflows based on certain business rules,
increasing leads strike rate by 16% compared to the existing leads workflow.
 Querying, cleaning, processing and modelling data using SQL and Python libraries, Pandas and
ScikitLearn
 Developed a clustering model based on K-means algorithm and data mining techniques to segment
customers by certain important indices, increasing product sales by 30% as marketing became more
targeted.
 Steered transformational change in the delivery of valuable insights to drive senior management
decision-making capabilities, utilising complex SQL queries and implementation of well-detailed
interactive Power BI dashboards, increasing staff productivity by 22%.
 Refactored old and slow SQL and Python codes to improve computational performance on large
datasets.
 Created and Monitored Business Intelligence Dashboards, KPIs and other indicators using SQL and
Advanced DAX functions by gathering, cleaning and formatting data from multiple sources.
 Contributed to development of quality control metrics for data acquired from the Data Warehouse;
formed strategy to cleanse the data, fill the missing values and remove outliers, resulting to about 80%
good quality data.