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Data & Analytics, Retail Technology, Marketing & Advertising

Senior Data Scientist (P4528)

Chicago, Illinois, United StatesOnsiteFull TimeSenior$97,000–$166,750 /yrPosted 2 months agoVisa sponsorship available

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Role summary

84.51° is seeking a Senior Machine Learning Engineer to join their Supply Chain, Operations, and Replenishment (SCORe) team. This role focuses on contributing robust code to a multi-contributor package supporting optimization sciences within the supply chain. Responsibilities include developing and supporting MLOps, implementing software solutions with best practices, and collaborating with cross-functional partners. The ideal candidate will have a Bachelor's degree, 2+ years of experience in ML/optimization model development, proficiency in Python, and experience with data wrangling and database querying. Grocery or supply chain experience is a plus.

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.

*84.51° follows a 5‑day in‑office work schedule to support collaboration, alignment, and team connection.*

Join us at 84.51°!

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Senior Machine Learning Engineer (P4528)

Summary

The Supply Chain, Operations, and Replenishment (SCORe) team is seeking a Senior Machine Learning Engineer (MLE) to support supply chain workstreams, focusing on contributing robust, well-tested code to a multi-contributor package that supports optimization sciences. This role combines foundational software development capabilities, applied ML and optimization research, and package design to scale to the enterprise. You will contribute code daily and collaborate with cross-functional partners to define, deliver, and scale supply chain optimization sciences.

Responsibilities

  • Lead the development and delivery of analytical plans to support client roadmaps, ensuring the adoption of best practices and innovative ideas.
  • Scope and manage work from inception to completion, ensuring timely delivery to specifications.
  • Develop and support MLOPs for production sciences.
  • Collaborate with stakeholders to understand client objectives and customer insights, designing best-in-class solutions.
  • Partner with engineering, product, and research teams to implement best practices for analysis, storage, and quality assurance.
  • Implement software solutions using best practices of coding standards and quality assurance with regards to maintainability and testing.
  • Identify opportunities for standardization and automation of existing solutions/processes, contributing to enhancements that maximize team potential and stakeholder value.
  • Interpret business results and develop actionable recommendations from data analysis to build relevant customer stories for stakeholders.
  • Challenge and improve 84.51° analytic capabilities, solutions, and best practices.
  • Follow best practices in space/resource management to ensure efficient utilization of analytic resources and timely delivery of business deliverables.
  • Partner with leaders across projects to prioritize work, identify risks and opportunities, and streamline team execution.
  • Support the near real-time science delivery of optimization models.

Qualifications, Skills, and Experience

  • Bachelor's degree in mathematics, statistics, analytics, data science, or a related discipline.
  • 2+ years of experience using advanced algorithms, programming languages, or technologies to develop technical analytics solutions or capabilities.
  • 2+ years experience developing and implementing enterprise-scale machine learning and/or optimization models.
  • Proficiency in querying data from relational databases.
  • Experience using Python, or similar statistical software to develop analytical solutions.
  • Expertise in data wrangling, data cleaning and preparation, and dimensionality reduction.
  • Ability to create computationally efficient solutions.
  • Strong analytical, creative problem-solving, and decision-making skills.
  • Strong business acumen; grocery and/or supply chain experience is a plus.
  • Passionate about data, analysis, and insights.
  • Natural curiosity that embraces change and a willingness to try new things and learn from failure.
  • Ability to work in a highly collaborative environment.

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