Lead Data Scientist - Enterprise Pricing & Promotion (P1606)

Cincinnati, Chicago, New York, Portland, Deerfield

SUMMARY:

We are a community of Data Scientists and Engineers that work to improve the shopping experiences of our customers, both in-store and online. This Lead Data Scientist role requires a unique mix of software engineering and data science skills necessary to create, deploy and maintain computationally efficient optimization implementations, frameworks, and end-to-end solutions. This role requires a strong understanding of math, algorithms, machine learning and data pipelines that will scale across many users and/or large, complex, and diverse data sets.

The role is for a Lead Data Scientist on the Enterprise Pricing & Promotions (EPP) team. EPP has a long-term focus to optimize pricing and promotion decisions at Kroger, including regular pricing, temporary price reductions, in-store promotional displays, weekly ad, and the various promotion tactics that our customers use to manage their grocery budgets. The role will support the deployment and maintenance of EPP’s cutting-edge prescriptive solutions that Kroger uses to establish optimal prices and promotions to drive multiple, simultaneous business objectives.

RESPONSIBILITIES:

• Lead the deployment, automation, and maintenance of cutting-edge Pricing & Promotion solutions that leverage machine learning and optimization techniques

• Develop and contribute to the Pricing & Promotion core optimization package using modular programming methods

• Build, steward, and maintain production-grade solutions to manage and serve machine learning and optimization models
• Scale and maintain machine learning and optimization solutions using best practices in DevOps and MLOps
• Collaborate with 84.51° and Kroger Product and Engineering teams to scale Pricing & Promotion solutions
• Understand business requirements to manage trade-off across scale, risk, and accuracy to maximize value

• Supervise and mentor junior Data Scientists in deploying analytical solutions and their integration into products
• Adhere to stringent quality assurance and documentation standards (GitHub, Sphinx, Confluence)

• Drive organizational innovation based on progress being made via academic and industry best practices

QUALIFICATIONS, SKILLS, AND EXPERIENCE:

• Bachelor’s degree or higher in Computer Science, Operations Research, Applied Statistics, or related field
• 4 years of experience using advanced algorithms, programming languages, or technologies
• 2 years of experience developing cloud-based software solutions and understanding of design for scalability, performance, and reliability
• 4 years of experience in tech consulting, retail or related professional services is preferred
• Experience developing and deploying solutions using Optimization methods is a plus
• Strong skills in Python, Spark, and cloud technologies
• Experience developing software using SDLC best practices, while leveraging CI/CD and MLOps to develop, test, and deploy
• Experience with technologies such as Azure, Spark, Databricks, Automation tools & MLOPS tools
• Experience building large-scale algorithmic solutions and deploying within a live production environment
• Comfort with independent learning of new technologies, and willingness to use unfamiliar tools
• Ability to work in a collaborative, cross-functional (Product, Engineering, Data Science) environment
• Strong project management skills and ability to manage multiple, simultaneous priorities when necessary
• Excellent communication skills, particularly on technical topics

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