Lead Data Scientist, Supply Chain

Overview

As a Lead Data Scientist, you will be responsible for leading role-specific project work as a part of a larger cross-functional team in support of one or more lines of business. Lead Data Scientists typically leverage and implement pre-defined analytics patterns and infrastructure on projects that are moderately complex, requiring working knowledge of limited set of machine learning, optimization, simulation, or other advanced modeling approaches. They must be able to quickly learn new subject-matter in support of a specific project or task. Our Lead Data Scientists typically work with latitude for action or decisions on specific projects, solutions, or technical issues. 

 

Successful candidates for this role must have strong analytical and research skills, a strong understanding of statistics and statistical modeling, an understanding of modern machine learning and its mathematical underpinnings, and they must have moderate programming skills with SQL, R and/or Python. They will need to be fast learners with a keen eye for detail, systems thinking, and process design. They must be team players who work steadfastly to create impactful change. This is a professional track role.

 

Our Flexible Future model offers a healthy mix of working in person and virtually, strengthening key elements of the Chick-fil-A culture by fostering collaboration and community. 

Responsibilities

The person who fills this role will be expected to do the following as a part of their regular work responsibilities:

• Leads the development and implementation of predictive and prescriptive models to improve supply chain operations
• Acts as an individual contributor on project engagements and is responsible for implementing data science best practice in their work
• Owns and is accountable for model and code quality and documentation for the project work they execute
• Collaborates with stakeholders to understand business needs and integrate optimization solutions into supply chain processes
• Analyzes large datasets to identify opportunities for supply chain improvements
• Applies machine learning, statistical methods, and operations research techniques to optimize supply chain performance
• Communicates complex optimization concepts and results to non-technical stakeholders
• Stays abreast of the latest developments in data science and optimization methodologies

Minimum Qualifications

• Bachelor's Degree in a Quantitative or Technical Degree Program and 3.2 GPA
• 3-5+ years of relevant experience
• Has strong analytical and research skills
• Has a strong understanding of statistics and statistical modeling
• Has an understanding of modern machine learning, simulation, and optimization underpinnings
• Has moderate programming skills in SQL, R and/or Python
• Has the skill to partner with cross-functional teams using strong written and verbal communication
• Is a fast learner and a proven 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
• Has a steadfast focus on creating impactful change

Preferred Qualifications

• Master's Degree in Operations Research, Industrial Engineering, Data Science, or a related field with a 3.2 GPA   
• 5+ years of relevant experience
• Has experience using AWS and/or Databricks for modeling
• Has experience using Github or similar version control system for managing code
• Has experience in machine learning using open source packages in Python
• Has some experience in simulation using Anylogic or similar software

Minimum Years of Experience

3

Travel Requirements

10%

Required Level of Education

Bachelor's Degree

Preferred Level of Education

Master's Degree

Major/Concentration

Operations Research, Industrial Engineering, Data Science, or a quantitative/technical related field

Minimum GPA (4.0 Scale)

3.2