Caesars Analyst Rotation Program Prep

What is a Primary Key?

• Can’t be duplicated

• Can’t be blank/null

• Each table can only have one primary key

What is a join table

A SQL operation that combines rows from two or more tables based on a related column between them. Joins help retrieve data that is spread across multiple tables.

What are the types of joins

• Inner Join

• Full Outer Join

• Left Outer Join

• Right Outer Join

Inner Join

• Returns only rows with matching values in both tables.

• Excludes any rows without a match.

• Most common join type.

Left Outer Join

• Returns all rows from the left table,
  and matching rows from the right table.

  • If there’s no match, the right table’s columns show NULL.

Right Outer Join

• Returns all rows from the right table,
  and matching rows from the left.

• Non-matching rows from the left = NULL.

  • Used less often

What is SQL

Language used to manage and manipulate data in a relational database

What is MySQL

Platform that implements SQL to store, retrieve, and manage data.

Tell me about yourself

I am a former student at UNLV where I graduated with Bachelors in Business Administration with a concentration in information systems. I currently work at NV Energy as a Contract Buyer, where I use Excel daily to track vendor pricing, manage purchase orders, and build data trackers to monitor cost trends.

Before that, I interned with NV Energy’s Supply Chain team, where I analyzed supplier performance and found process improvements that reduced costs by about 45%. I also worked in IT, where I learned how to troubleshoot systems and communicate with technical and non-technical teams.

Those experiences helped me realize how much I enjoy using data to solve business problems. That’s why the Caesars Strategic Analytics Rotational Program really excites me — it’s the perfect environment to keep learning, apply data-driven thinking across gaming, hospitality, and digital operations, and grow into a well-rounded analyst.

Tell me about a time you improved a process

Definitely, around July, our company went through a system migration from PeopleSoft ERP to Oracle Fusion. The transition significantly changed many of our workflows, especially for buyers like myself who needed to obtain supplier quotes for materials.

Before the migration, buyers received automated supplier recommendations within the system. After the migration, that functionality was no longer available. This meant we had to manually research items and find distributors, which could take around 10 minutes per item — not ideal when processing over 50 requisitions a day.

To address this, I collaborated with our analytics team, who shared an Excel dataset containing over 11,000 item IDs and their approved manufacturers. However, the dataset wasn’t formatted for easy lookup. I cleaned and restructured the data, then used Excel functions like VLOOKUP, TEXTJOIN, and IF statements to consolidate multiple approved manufacturers into a single cell for each item ID.

As a result, I built an excel tool where I could simply enter an item ID and instantly retrieve all approved manufacturers. This reduced the quote-gathering process from roughly 10 minutes per quote to 10 minutes for 20+ quotes, improving our efficiency by more than 95% and ensuring compliance with approved supplier lists.

Tell me about a time you used data to make a recommendation

During my internship at NV Energy, our director asked me to analyze two years of item purchase history to identify suppliers who sold similar products within the same category. The goal was to find opportunities for supplier consolidation and cost savings.

Using Excel, I cleaned and grouped the data by item category and supplier, then calculated key metrics such as the total spend and number of purchase orders per supplier. Once I identified patterns, I created a summary showing the top five suppliers by both spend and order volume.

I shared these insights with my director, who used the data to make informed decisions on consolidating supplier relationships. This helped the team reduce redundancy in purchasing, streamline supplier communication, and uncover potential cost savings opportunities.

How do you handle multiple deadlines

I prioritize deadlines by urgency and impact. I typically create myself an agenda with tasks that I need to complete within the day. Personally, I like to focus on tasks that require the most time to complete first and then focus on simpler tasks after.

I also like to set myself my own internal checkpoints to make sure that I stay on track.

Biggest Strength

My curiosity and willingness to learn from my mistakes

Biggest Weakness

My lack of exposure to certain applications in a professional setting. For example, I’ve only had academic exposure to python.

Difference between Excel and SQL

• Excel - smaller ad hoc analysis and visuals

• SQL - querying and combining large datasets from databases

When would you use a pivot table

Summarize large data quickyC

Common Excel Functions for analysts

SUMIFs, AVERAGEIFS, COUNTIFS, VLOOKUP, INDEX-MATCH, IF, and TEXT functions for cleaning data

What does GROUP BY do

Groups rows by a column so you can aggregate for each group - total sales per region

Difference between WHERE and HAVING?

Where filters rows before aggregation; HAVING filters aggregated groups after GROUP BY

What is data normalization

Organizing data into related tables to reduce duplication and improve consistency.

How would you measure a marketing campaign’s success

Compare campaign vs control groups: redemption rate, conversion, ROI, and repeat visits.

What would you do if data was incomplete or inaccurate?

Assess how much is missing, clean or impute if small, exclude if too biased. Document limitations before drawing conclusions.

How would you use data to improve the guest experience?

Analyze Caesars Rewards behavior to personalize offers and spot pain points — for example, target frequent guests with specific amenities or sports promos.

If two team members disagree on how to approach a project, what do you do?

Refocus on the goal and data. Compare both approaches objectively and choose what best answers the business question.

What would you do if data contradicted leadership’s intuition?

Show the findings visually, explain your method, and frame it as insight to help decision-making rather than a challenge.

How do sportsbooks use data?

They model odds, track user engagement, balance risk, and measure promotion ROI — the goal is profitable engagement while managing exposure.

What’s a key metric for casino operations?

“Win per unit per day — it shows how much revenue each slot or table generates daily.”

What’s the difference between correlation and causation?

“Correlation means two things move together; causation means one causes the other. For example, occupancy and F&B sales are correlated, but seasonal demand might cause both.”

How would you ensure your analysis is accurate?

“I’d double-check data sources, validate calculations with a small sample, and compare results to prior reports or benchmarks before sharing conclusions.”

How do you think analytics drives value at Caesars?

“Analytics drives smarter decisions — from optimizing hotel rates and marketing campaigns to improving player experiences in gaming and sportsbook. It connects every part of the business with measurable insight.”

What’s one KPI you’d track for hotels?

“RevPAR (Revenue per Available Room) — it reflects both occupancy and pricing power, so it’s a great indicator of hotel performance.”

What kind of insights can Caesars get from loyalty data?

“They can identify guest preferences, predict high-value customers, and design offers that increase retention and total spend across properties.”

How do you communicate data to non-technical stakeholders?

“Keep it simple — focus on what the numbers mean, not the formulas. Use visuals, summarize key takeaways, and always connect insights to business goals.”

How do you handle learning a new tool like Tableau or Python?

“I dive in by practicing on real data. That’s how I learned Excel — I built actual trackers at work. I’d take the same approach with Tableau or Python.”

What do you hope to gain from the rotational program?

“I want to explore different areas of analytics to see where I create the most impact — and to develop both my technical and business understanding before specializing.”

Where do you see yourself in 3–5 years?

“Growing into a full-time analyst or senior analyst at Caesars, ideally focusing on data strategy or product analytics — helping teams make data-driven decisions.”

RevPAR (Revenue per Available Room)

Total room revenue ÷ total available rooms — combines price & occupancy performance.

“We’d track RevPAR to measure hotel profitability across properties.”

ADR (Average Daily Rate)

Average room revenue earned per occupied room.

“A drop in ADR might show we discounted too aggressively.”

Occupancy Rate

% of available rooms that are sold

“High occupancy with low ADR might mean we’re filling rooms but underpricing.”

Yield Management / Dynamic Pricing

Adjusting room or ticket prices based on demand.

“We use dynamic pricing to optimize weekend vs. weekday rates.”

F&B

Food & Beverage — major revenue driver for resorts.

“F&B spend per guest can indicate guest satisfaction and loyalty.”

Guest Mix

The proportion of leisure, business, and loyalty guests.

“Our guest mix shifted toward leisure travelers post-COVID.”

Comp Rooms / Complimentary Offers

Free rooms given to high-value players or loyalty guests.

We analyze comp redemption rates to measure promotional ROI.”

Customer Lifetime Value (CLV or LTV)

Total profit expected from a customer over time.

“We prioritize offers for guests with high lifetime value.”

Churn / Retention Rate

How many customers stop vs. continue visiting.

Reducing churn by 5% can drive major revenue gains.”

Gross Gaming Revenue (GGR)

Handle minus payouts — total profit from bets.

Bet Conversion Rate

% of users who place a bet after visiting the site.

Regression Analysis

Measures relationships between variables.

“We can use regression to see how room price, loyalty tier, and day of week affect occupancy.”

Correlation

Strength and direction of a relationship (-1 to +1).

“Spend and visit frequency usually have a strong positive correlation.”

Time Series Forecasting

Predicting future trends based on historical data.

“We could forecast hotel demand by analyzing seasonal patterns.”

Root Cause Analysis

Digging into what drives a change or anomaly.


“If hotel revenue drops, I’d isolate whether it’s due to occupancy, pricing, or seasonality.”

Cohort Analysis

“We could track guests who joined Caesars Rewards in Q1 to see retention after 6 months.”