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

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.

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; Build strong working relationships within the immediate team and cross-functional partners

Requirements

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

Nice to have

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

Benefits

medical, dental, vision, legal, and accidental death and dismemberment insurance; FSA/HSA (depending on enrolled medical plan); short-term disability; long-term disability; life insurance; 401(k) plan; 4 weeks of vacation; paid sick leave; 10 paid holidays; floating day off; half day Fridays year-round; 2 paid days for volunteer time each calendar year