Little Caesars is looking to leverage data science solutions, including AI/ML, to drive the development of best-in-class data science capabilities. The goal is to enable data-driven decision-making to make the company even better.
Requirements
- Capability to develop data science solutions in SQL, R, and/or Python, as well as utilize and adapt open-source solutions
- Experience with machine learning, artificial intelligence, and advanced methodologies in key areas of the LCE/IHI business, like pricing, forecast predictions, optimization, etc.
- Experience with processes and tools (including embedded features) that secure data security and data privacy
- Knowledge of how on-prem and cloud data storage factors in the design of data science solutions
- Understanding modern ways of working/ product development such as Agile, Design Thinking, MLops
- Experience in Databricks, Jupyter notebooks, as well as Azure Data Factory
- Capability to support the deployment of solutions in additional programing languages and applications
Responsibilities
- Support LCE/IHI decision makers across levels, geographies, etc. with key analytics products like, predictive analytics model, recommendation engines, attrition/retention models, large scale optimization engines, as well as key analytics techniques like multivariate testing – to name a few
- Create and contribute to the development of team structures that are adaptable as we grow and scale the data science work (e.g., MLOps, Data Engineering, Product Owners, etc.)
- Develop and adhere to the best practice in data science across the companies and functions and actively share knowledge and data assets with decentralized data and analytics resources
- Leverage the key drivers of our business through the building of advanced analytics products that enable business leaders to know with confidence the best path forward
- Partner with infrastructure, data warehouse and data engineering colleagues to address the immediate needs identified in the development of business focused analytics products and build a future landscape that enables deeper analytics at greater speed
- Partner with the leaders and coworkers in centralized data functions, like Data Governance and BI to support the efficient built-out of the data and reporting infrastructure that supports all analytics
- Highlight opportunities to use new data sources and new data science tools that are value-adding and cost effective
Other
- Masters in Data Science or undergrad in quantitative studies with 2+ years of Data Science practice OR 5+ years Undergraduate in Data Science or undergrad in statistics, mathematics, computer science, or similar fields of study with 5+ years of Data Science practice
- Proficiency to convey, in simple terms complex mathematical and statistical concepts and how they relate to the business challenge
- Accomplished in analyzing business challenges and developing solutions through cross-functional collaboration
- Proficiency to communicate findings in an audience adapted way, including through compelling visualizations
- Practiced in bringing structured thinking in ambiguous problems spaces and delivering solutions
