THE OPPORTUNITY
Are you driven to create mathematical models that move business forward? Are you excited to see a Fortune 500 company utilize your models? If so, we may have the ideal opportunity for you! Dillard’s is seeking a Data Scientist I in Prescriptive AI to join our team in Little Rock, AR. As a Data Scientist I, you will contribute to business improvements by helping to make data-driven, optimal decisions. To be successful in this role, you must be able to work efficiently on your own as well as part of a team.
THE TEAM
As a Data Scientist I in Prescriptive AI, you will be a part of a team that collaborates with many areas of
the business is to develop and implement decision models to make Dillard’s more profitable and efficient.
This role reports to the Manager of the Predictive/Prescriptive AI. This is an excellent opportunity to work with an exceptional team of Operations Researchers and Data Scientists. This role provides cross--
training and experience in different fields of AI, including Gen AI.
WHAT YOU WILL DO
- Learn and maintain current applications and models in production
- Make necessary adjustments to the models, test them, and deploy them in production while keeping feedback from various business units
- Develop mathematical models using optimization techniques and implement them in Python, test your scripts in the development environment, and deploy them in production
THE MUST-HAVES
- BS in Operations Research, Industrial Engineering, Applied Mathematics/Statistics, Computer Science, or a related field, or exposed to mathematics/statistics-related courses/topics
- Beginner to intermediate experience in SQL
- Beginner to intermediate experience in Python
- Exposed to the projects/concepts that include mathematical/statistical concepts
- Creativity, innovation, and idea generation
- Clear, concise communication with professional presentation design and delivery
- Ability to work onsite at Corporate Headquarters in Little Rock, AR, during established hours
- Authorization to work in the United States without sponsorship
THE NICE-TO-HAVES
Experience in:
- Developing operations research (optimization) models
- Supply chain and/or retail
- Using Gurobi and/or CPLEX Optimizer
- Discrete event simulation
WITHIN 1 MONTH, YOU’LL
- Be comfortable with Data Warehouses, Teradata, and DB2, including understanding the structures of basic and commonly used data within the team
- Be able to write SQL queries in Teradata and DB2 to retrieve the data needed (SQL training)
- Be exposed to AI Cluster
- Be comfortable with basic Linux commands (survival guide)
WITHIN 2 MONTHS, YOU’LL
- Be comfortable with Dillard’s AI Cluster in developing, running, and scheduling spark and non-Spark Python scripts
- Be comfortable with basic GitLab commands
- Be able to create simple Python packages (creating wheel files)
- Be able to write Python scripts to pull and push data from and to data warehouses
WITHIN 3 MONTHS, YOU’LL
- Be able to write Python scripts to run simple optimization models
- Have a good understanding of demand forecasts and how they are done at a high level from
- Predictive AI team (Traditional AI)
- Have a good understanding of the needs of the Supply Chain Analytics team (SCA) and Replenishing Team
- Have a good understanding of basic replenishment rules
- Have a good understanding of (non-allocation model-related) production jobs
- Be able to create branches in GitLab to test your changes to the production job
WITHIN 6 MONTHS, YOU’LL
- Be exposed to allocation models
- Have a good understanding of the structure of the internally developed Python package of
- Have a good understanding of one of the most frequently used allocation models
- Be able to create branches in GitLab to test your changes to the allocation model
- Be able to answer SCA requests and troubleshoot the allocation model with quick turnaround times
- Be able to collaborate with the team on a new project