Sr. Analyst, Operations Analytics, Burger King

Restaurant Brands International•Miami, FL

43d•Onsite

About The Position

The Sr. Analyst, Operations Analytics plays a key role in improving restaurant performance, operational efficiency, and the guest experience through data-driven insights. This role is responsible for analyzing key operational metrics, identifying performance trends and opportunities, and developing reporting tools and lightweight applications that enable informed decision-making across the business. The Sr. Analyst partners cross-functionally with Operations, Brand Standards, Brand Execution, Field Execution, Training, Marketing, Digital, and Finance to translate complex data into actionable insights and recommendations. This role also supports the design and evaluation of operational initiatives, ensuring strategies are grounded in reliable data and aligned with broader business objectives. The role combines SQL and Python fluency with strong business judgment, and expects current AI tooling and automation to be part of everyday analytical work. We are looking for someone who treats recurring manual work as a problem worth solving rather than a fixed cost of the job.

Requirements

3+ years of experience in an analytical role within Operations, Marketing, Finance, Business Analytics, or a related function.
Bachelor’s degree in Business, Data Science, Statistics, Finance, Analytics, or a related field.
Strong SQL skills and experience working with cloud data warehouses; Snowflake experience preferred.
Proficiency in Python for data analysis and automation, including independently writing and debugging scripts; Streamlit or similar experience is a plus.
Strong troubleshooting skills with the ability to identify and resolve data, logic, query, and reporting issues.
Hands-on experience using AI tools such as ChatGPT, Claude, or Gemini for analytical workflows, coding, automation, and productivity, with a strong approach to validating AI-generated outputs.
Familiarity with experimental design and statistical analysis, including control groups, sample sizing, and assessing statistical significance.
Strong data storytelling skills, including creating executive-ready Excel, PowerPoint, and analytical deliverables.
Strong analytical and business judgment with the ability to translate complex data into actionable insights and recommendations.
Self-directed and intellectually curious, with a demonstrated ability to quickly learn and apply new tools and technologies.
Strong communication, organization, and cross-functional collaboration skills, with the ability to manage multiple priorities in a fast-paced environment.

Nice To Haves

Streamlit or similar experience is a plus.
Experience programmatically applying large language models to analyze, classify, summarize, or structure data is a plus.

Responsibilities

Analyze restaurant-level operational metrics, including guest satisfaction, speed of service, brand audits, and training completions, to identify performance trends, opportunities, and areas of underperformance.
Conduct root cause analyses to understand performance gaps and develop data-driven recommendations to improve restaurant operations and the guest experience.
Design and evaluate market tests and operational pilots, including test and control group construction and sample sizing, and measure results to inform future business decisions.
Build, maintain, and enhance reporting and analytical tools in Snowflake and Python, including internal applications and automated reporting that replace manual, recurring processes.
Prepare recurring performance reporting on key operational metrics, including drive-thru utilization, hours of operation, and guest satisfaction, and support ad hoc analyses and strategic projects, developing presentations and recommendations for senior leadership.
Propose and implement improvements that remove manual, repetitive, or error-prone work from the team's analytical workflows, using Python, Snowflake, and AI tooling. Document and share working approaches so improvements compound across the team rather than living with one analyst.
Investigate data discrepancies and unexpected results, tracing issues through queries and source tables to identify root cause, and partner with RBI's data teams to resolve upstream problems and confirm the fix held.
Own data quality for team reporting: onboard and validate new data sources and vendor feeds, maintain metric continuity through vendor or survey instrument changes, and document metric definitions and query logic so analyses are reproducible by others.
Partner cross-functionally with Operations, Brand Standards, Brand Execution, Field Execution, Training, Marketing, Digital, and Finance, and collaborate with franchisee partners to understand business needs and support execution of key operational initiatives.
Apply text and sentiment analysis to extract themes from unstructured guest comments at scale.