Senior Data Scientist, Personalization Analytics

MGM Resorts; Nevada; Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Wellness incentive programs

Hotel, F&B, retail, and partner travel

Free parking

Health & Income Protection

Professional development

Volunteer opportunities

Job summary

MGM Resorts International is seeking a Senior Data Scientist to join its Commercial Data Science team within Marketing. This hands-on role develops and evolves AI/ML models and orchestrates them to drive customer engagement and business value.

You will work on end-to-end data science tasks—from data munging and feature engineering to deployment, A/B testing, and KPI measurement—collaborating with analysts, engineers, and business partners.

Qualifications

• Bachelor's Degree required
• 5+ years of relevant experience
• MS/PhD preferred
• Experience with agile/sprint-based approaches preferred
• Hospitality, retail, or customer-service industry experience preferred

Responsibilities

• Contribute to multiple complex Data Science projects independently
• Develop and implement AI/ML models and orchestration
• Enhance personalization and commercial strategies with data science models
• Develop predictive and statistical models and deploy them
• Collaborate with data scientists, analysts, and engineers on data requirements
• Create insights reports and present results to stakeholders
• Develop A/B test framework and evaluate model quality

Skills

AI/ML Modeling

Feature Engineering

Statistical Modeling

Experimentation

Agile Methodology

Communication

Education

Bachelor's degree in CS/Engineering/Math

MS/PhD preferred

Tools

Python

SQL

R

CI/CD

Job description

MGM Resorts International is seeking a Senior Data Scientist to join its Commercial Data Science team within Marketing. This hands-on role develops and evolves AI/ML models and orchestrates them to drive customer engagement and business value.

You will work on end-to-end data science tasks—from data munging and feature engineering to deployment, A/B testing, and KPI measurement—collaborating with analysts, engineers, and business partners.