Data Scientist (Strategic Insights)

Overview

As a Principal Data Scientist, you will be responsible for leading and executing the most technically complex data science project work in support of multiple disciplines and lines of business within Restaurant Development. The person in this role will work as part of a larger, cross-functional, full-stack execution team charged with designing, building, and deploying, and monitoring advanced analytics products and models for Restaurant Development (RD).

This individual will also serve to set the long-term vision and strategy for advanced analytics capabilities for Restaurant Development.

The Principal Data Scientist will leverage expert exploratory data analysis skills to analyze and integrate a wide range of data in preparation for then applying or developing any needed methods, models, algorithms, and/or simulations to the most complex business or technical problems. They must be able to quickly learn new subject-matter in support of a specific project or task. They will also typically be expected to develop and demonstrate a high level of proficiency in multiple skill specializations across data science sub-disciplines (like causal inference, forecasting, simulation, optimization, machine learning, or deep learning, geospatial).

• The person who fills this role will be expected to do the following as a part of their regular work responsibilities:
• Analyzes data and applies or develops any needed methods, models, algorithms, and/or simulations to solve the most complex business or technical problems.
• Serve as a subject matter expert (SME) to provide long term vision and planning for advanced analytics capabilities in Restaurant Development in conjunction with internal stakeholders.
• Demonstrates proficiency in multiple sub-disciplines within data science, such as causal inference, forecasting, simulation, optimization, machine learning, an/or deep learning and geospatial.
• Works as a part of a virtual full-stack execution team comprised of data engineers, data scientists in RD and Enterprise Data &Analytics, and technical product owners of geospatial technologies.
• Works closely with data engineers to define data requirements, evaluate source data quality, determine needed data transformations, execute candidate feature engineering, and select features for inclusion in candidate models.
• Leverages the Model Ops toolchain to develop models for production by Deployment Engineers.
• Works closely with Deployment Engineers to refactor model and feature code for deployment via the Model Ops toolchain, to test the model workflow pre-deployment, and to deploy and evaluate the model workflow into production.
• Works closely with Technical Product Owners in GIS to understand, develop, and support advanced analytics work.
• Coordinate, communicate, and train end users and stakeholders about the advanced analytics products and how to effectively use them to make decisions, explaining the nuances of the models.
• Manages any needed maintenance, retraining, or quality control on models they have built which are actively in production.
• Owns and is accountable for model and code quality and documentation for the project work they execute.
• May lead the work of more junior data scientists and of 3rd party contingent or contract resources.

• 8 years of work experience
• Master's Degree in Quantitative or Technical Degree Program
• Has very strong analytics and research skills.
• Has expert exploratory data analysis (EDA) skills.
• Has a deep understanding of statistics and statistical modeling.
• Has a strong understanding of the modern machine learning and its mathematical underpinnings.
• Has very strong programming skills in SQL, and in R or Python.
• Experience with geospatial libraries and tools.
• Can partner well within a cross-functional team.
• Has strong written and verbal communication skills.
• Is a fast learner and problem solver.
• Has a keen eye for system thinking and process design, especially with respect to scalability and automation.
• Has a keen eye for detail and thoughtful investigation of data.

• Ph.D. in Quantitative or Technical Degree Program
• Has some experience using the AWS big data technology stack.
• Has some experience developing production ready machine learning or advanced statistical models.
• Has demonstrated proficiency in one or more sub-disciplines of data science, like causal inference, forecasting, simulation, optimization, machine learning, or deep learning, geospatial.
• Has some experience with Model Operations tools and processes.
• Experience with geospatial libraries and tools. (Data Bricks and ESRI preferred).