Data Scientist (AI/ML Modeling, Forecasting and Algorithms)

Yum! Brands; Louisville (KY); On-site; USD 106,600 - 133,200; Full time

Benefits offered by this job

4 weeks vacation

Paid sick leave

10 paid holidays

Floating day off

Half day Fridays year-round

2 paid volunteer days per year

Job summary

Yum Crave AI in the United States is seeking a Data Scientist to advance AI/ML modeling and algorithm development for operational and business needs. In this role you will work on moderately complex modeling assignments, applying established data science techniques to deliver scalable AI/ML solutions in partnership with cross-functional teams.

This role is ideal for a data scientist who is strengthening their expertise in applied modeling and progressing toward senior-level ownership.

Qualifications

• Bachelor’s or Master’s degree in a quantitative field.
• 2+ years of experience in data science or machine learning.
• Experience applying machine learning techniques to real-world problems.
• Proficiency in Python and SQL.
• Understanding of model evaluation metrics and validation approaches.

Responsibilities

• Develop and implement machine learning models using established approaches (regression, classification, forecasting, optimization).
• Translate business and operational requirements into structured modeling problems with guidance from senior team members.
• Perform feature engineering, model training, validation, and evaluation using defined best practices.
• Contribute to improving existing models and pipelines.
• Support the design and analysis of experiments (e.g., A/B tests, simulations) under guidance.
• Monitor model performance and identify opportunities for improvement.
• Apply standard processes to assess model quality, accuracy, and reliability.
• Work with structured and semi-structured datasets to prepare data for modeling.
• Write clean, maintainable Python and SQL code.
• Partner with Data Engineering and ML Engineering to support model deployment.
• Clearly communicate analytical findings to technical and non-technical stakeholders.
• Document assumptions, methodologies, and results.

Skills

Communication

Team collaboration

Analytical thinking

Education

Bachelor’s or Master’s degree in a quantitative field

Tools

Python

SQL

TensorFlow

PyTorch

AWS/GCP/Azure

Job description

Yum Crave AI is seeking a Data Scientist (AI/ML Modeling & Algorithms) to support the development and implementation of machine learning models that address operational and business needs. In this role, you will work on moderately complex modeling assignments, applying established data science techniques to deliver scalable AI/ML solutions in partnership with cross‑functional teams.

This role is ideal for a data scientist who is strengthening their expertise in applied modeling and progressing toward senior‑level ownership.

AI / ML Model Development

• Develop and implement machine learning models using established approaches (regression, classification, forecasting, optimization)
• Translate business and operational requirements into structured modeling problems with guidance from senior team members
• Perform feature engineering, model training, validation, and evaluation using defined best practices
• Contribute to improving existing models and pipelines

Experimentation & Model Evaluation

• Support the design and analysis of experiments (e.g., A/B tests, simulations) under guidance
• Monitor model performance and identify opportunities for improvement
• Apply standard processes to assess model quality, accuracy, and reliability

Data & Technical Execution

• Work with structured and semi‑structured datasets to prepare data for modeling
• Write clean, maintainable Python and SQL code
• Partner with Data Engineering and ML Engineering to support model deployment

Collaboration & Communication

• Clearly communicate analytical findings to technical and non‑technical stakeholders
• Document assumptions, methodologies, and results

Qualifications

Build strong working relationships within the immediate team and cross‑functional partners.

• Bachelor’s or Master’s degree in a quantitative field (e.g., Data Science, Statistics, Computer Science, Engineering, Mathematics)
• 2+ years of experience in data science or machine learning
• Experience applying machine learning techniques to real‑world problems
• Proficiency in Python and SQL
• Understanding of model evaluation metrics and validation approaches

Preferred Qualifications

• Exposure to deep learning frameworks (e.g., TensorFlow, PyTorch)
• Experience working in cloud environments (AWS, GCP, or Azure)
• Familiarity with experimentation methodologies (A/B testing)
• Experience collaborating with engineering teams on production deployments

Compensation and Benefits

Salary Range: 106,600 - 133,200

Employees (and their eligible family members) may enroll in the following types of insurance coverage: medical, dental, vision, legal, and accidental death and dismemberment, as well as FSA/HSA (depending on enrolled medical plan). Yum! also provides short‑term disability, long‑term disability, and life insurance. Employees may enroll in our 401(k) plan. Yum! provides 4 weeks of vacation, paid sick leave, 10 paid holidays, a floating day off, half day Fridays year‑round and 2 paid days for volunteer time each calendar year. To learn more about working at Yum! - Click here.

YUM! Brands, Inc. (including its subsidiaries Yum Restaurant Services Group, LLC (“YRSG”) and Yum Connect, LLC (“Yum Digital and Technology”)(collectively, “Yum”) is proud to be an equal opportunity employer and is committed to equity, inclusion, and belonging for all dimensions of diversity. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other protected characteristic. Yum! is committed to working with and providing reasonable accommodation to applicants with disabilities or special needs. US Job Seekers/Employees - Click here to view the “Know Your Rights” poster and supplement and the Pay Transparency Policy Statement.