My main focus has been on learning how machine learning algorithms fuction and how to best utilize them under different circumstances. To keep it short here is a list of technologies i have worked with:

1. ACL (Audit Command Language) - to crunch large amounts of data and create different analytics and reports for the Corporate Audit department i was in

2. R - used for more complicated calculations and projects (Customer Churn models, Outlier detection and so on)

3. Python - start to finish solutions for machine learning projects based around on a plethora of problems (Customer Churn, Customer Application completion, Deposit optimization, Revenue optimization, Outlier detection, Automation of workflows and sending notifications/reports to relevant parties, Database interactions)

4. PostgreSQL - very limited use due to the simplicity of the required database structures for the above projects.