United Interview Prep

United Mission

“Connecting People, Uniting the World”

United Pillars

Safety, Caring, Dependability

United Purpose

To bring people and communities together through its global network, while also driving decision-making that supports its values.

Why am I a good fit for this role?

That’s a great question!  From my research on the role and its requirements, I see that it requires 3 broad skill areas: operational analytics and insights, internal consulting, and professional development.  I am qualified because I have a lot exposure to analytical tools needed for this job to find inights given raw data, I have real-world consulting experience and I will have 20 more weeks of experience coming out of this school year, and this is the perfect opportunity to practice and apply my skills in a professional environment where my work has a real impact on operations.

How to analyze operational performance?

S - Start by understanding the operational question.

B - 1) Define the Problem (Performance slipping? Delays increasing?)

2) Identify the Key Inputs (time of day, duration, etc)

3) Clean and prepare data (so it’s reliable)

4) Explore the trends visually (dashboards, heatmaps, or time series - so I can see the patterns quickly)

5) Run a deeper analysis (segmentation/regression/correleation)

6) Use the finding to translate what’s happening operationally and potential solutions

R- Using these steps me move from raw data to clear, actionable insights. It’s how I found peak price patterns in the uber project and how we adjusted our recommendations.

How to clean and validate data?

S - Almost every analytics project I’ve done required me to clean data before I could start drawing insights

B - 1) Check for missing or inconsistent values (will I remove or correct them?)

2) Standardize the formats for time, text, and categories

3) Remove duplicates (and identify outliers that distort trends)

4) Make sure that everything is logical (like durations can’t be negative and all the timestamps make sense)

5) I would also keep track and document all the steps so that my analysis is transparent

R- prevents misleading conclusions. uber project → allowed us to correctly identify rush hours

What tools am i comfortable with (Python, SQL, and Excel)?

Python → cleaning large data sets, running regression/forcasting models, building interactive visualizations (using plotly)

SQL → for querying, filtering, joining, and preparing data before analysis. I built and designed databases in class using this tool.

Excel → my first intro to business analytics, i use it a lot when i collaborate with teamates who are less technical (my general business classes), and doing quick analysis, pivot tables, and dashboards.