Principal Data Scientist - New Restaurants

Overview

The Principal Data Scientist is a senior individual contributor responsible for defining and leading advanced analytical approaches to complex and ambiguous business problems. This role shapes modeling strategy and technical direction for high-impact analytics initiatives, primarily supporting Restaurant Development while influencing broader enterprise analytics capabilities.

Responsibilities

• Advanced Analytics & Modeling
• Define modeling approaches and analytical frameworks for complex or ambiguous problems where established solutions do not yet exist.
• Apply predictive modeling, forecasting, classification, clustering, and other advanced analytics techniques to large datasets.
• Explore and integrate diverse data sources including transactional, behavioral, demographic, geospatial, and operational data.
• Build and validate models using best practices for feature engineering, experimentation, and model evaluation.
• Translate analytical findings into clear insights and recommendations for business stakeholders.
• Technical Contribution
• Develop production-ready analytical models and support their integration into data platforms and business workflows.
• Identify modeling risks early, including bias, data limitations, drift, and statistical assumptions that could impact model validity.
• Collaborate with data engineers and analytics teams to ensure data quality, model reliability, and scalable implementation.
• Contribute to the development of reusable analytical frameworks, code libraries, and modeling workflows.
• Support the evaluation and selection of appropriate analytical techniques and tools for specific use cases.
• Document analytical approaches, model assumptions, and results to ensure reproducibility and transparency.
• Cross-Functional Collaboration
• Partner with business stakeholders to understand analytical needs and translate business questions into data science solutions.
• Communicate complex analytical results in a clear and concise manner to both technical and non-technical audiences.
• Contribute to cross-functional analytics initiatives and collaborate with engineering, product, and analytics teams.
• Provide guidance and knowledge sharing on modeling approaches and analytical methods within project teams.

Required Qualifications

• 6+ years of experience in data science, machine learning, or advanced analytics.
• Strong understanding of statistical modeling, machine learning algorithms, and predictive analytics.
• Proficiency in Python and SQL for data analysis and model development.
• Experience working with large datasets and modern data platforms.
• Strong problem-solving, analytical thinking, and communication skills.

Preferred Qualifications

• 8+ years of experience in data science, machine learning, or advanced analytics.
• Experience with machine learning frameworks such as PyTorch, TensorFlow, or similar tools.
• Experience with distributed data processing frameworks such as Spark.
• Exposure to cloud-based analytics platforms such as AWS, Azure, or GCP.
• Experience applying advanced analytics techniques such as geospatial analysis, optimization, or network modeling.

Required Years Of Experience

• 6

Preferred Years Of Experience

• 8

Travel Requirements

• 10%

Required Level Of Education

• Bachelor's degree or equivalent experience

Preferred Level Of Education

• Master's Degree

Required Major/Concentration

• Statistics
• Computer Science
• Applied Mathematics
• Data Science
• Engineering
• A related quantitative field

Relocation Assistance Provided

• No