This was my second internship with Southwest Airlines in its Dallas Headquarters. My previous internship was with Operational Strategy team which deals with On-Time Performance (OTP), Block Time Hit Rate (BTHR), Turn Time Compliance, Departure Performance and many other Operations specific KPIs. But along with all that it also made gave me curious about the airline industry as a whole; interdependencies of various departments. So, I continued my journey with Southwest Airlines but with a new team, Corporate Facilities – Baggage Handling as a Data Science Intern.  

I joined a 4 member team handling the Analytics front of corporate facilities. I was responsible for handling the complete Python front for predictions, designing new Alteryx and Tableau workflows, and development of new KPIs useful to Facilities. I was also responsible for analyzing the Baggage check-in time, customer wait time, the number of Kiosk or ticket counters needed and cart requirement at any point in time for any specific airport.

Thank you Hugo, Curtis, Meredith for this amazing experience. Thank you Daniel for this second opportunity and giving me an interview chance for this position.

But what exactly did I do? 

Good question- I did so much forecasting, it’s hard to combine everything together. So here are the small things:

Forecasting

• Various SWA Check-in Baggage and Customer related KPIs: These are station specific and varies with time.

• Analyze SWA stations with potential baggage related delays with influencing factors: Calculated the overflow for each time interval throughout the day based on everything analyzed above we tried to find any potential issues. Python code was robust enough to handle even larger stations.

Bug Fix

….and it’s never an easy task!

Production Time-Related Discrepancies: Due to Daylight Saving, UTC time difference, SWA app sync issues Did a thorough analysis of Tableau reports, SWA applications, Alteryx workflows; compared station specific date results using Alteryx- data blending. Created a generic solution and stored a table in Teradata to fix UTC difference w.r.t. various SWA stations

What did I get out of it?

The internship enabled me to understand the relationship between various departments, the criticality of data science in this ever-changing airline world. The technical side of the internship involved in developing models using python with database SQL queries embedded in the code, Alteryx for data massaging and visualization using Tableau and PowerPoint. This internship has shown me the importance of Big-Picture Thinking and has created a platform for advancing my knowledge as a Data Scientist.

It’s about the Journey, Not the Destination! Love doing something! –> keep doing it –> it will take you to the right destination