Lead Data Scientist

2 weeks ago

Cincinnati, United States 84.51° Full time
84.51° Overview:

84.51° is a retail data science, insights and media company. We help The Kroger Co., consumer packaged goods companies, agencies, publishers and affiliates create more personalized and valuable experiences for shoppers across the path to purchase.

Powered by cutting-edge science, we utilize first-party retail data from more than 62 million U.S. households sourced through the Kroger Plus loyalty card program to fuel a more customer-centric journey using 84.51° Insights, 84.51° Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.

Join us at 84.51°

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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