ML / Optimization Engineer (P1607)

Join to apply for the ML / Optimization Engineer (P1607) role at 84.51°

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°!

We are a community of analysts that act as the voice of the customer – they share their story with us each and every day. Through simple, comprehensive, purposeful analytics, we fearlessly bring these customer stories and journeys to life. Our 360° customer view allows us to anticipate customer needs, thus enabling our clients to connect with their customers in meaningful, relevant ways.

The Stores, Assortment, and Space (SAS) team is looking for a Senior ML Engineer to join the team. This role will focus on developing technical solutions to support assortment decision-making at Kroger, building packages and tools that will enable reliable and efficient execution and delivery of 84.51°'s best-in-class assortment data and sciences to internal and external stakeholders. The ideal candidate for this role should have strong technical skills and be comfortable collaborating cross-functionally with data scientists and data engineers to develop advanced analytical methods and scale them in production.

Responsibilities

• Experience implementing and evolving MLOps best practices
• Data engineering, automating ML workflows, experiment tracking, model registration, accuracy monitoring, model serving.
• Evolve or develop methodologies and solutions for assortment and space optimization
• Special focus is on item performance prediction models and optimization algorithms.
• Effective alignment of stakeholders and deliverables using documentation to ensure on-time delivery and acceptable output.
• Support the technical development of foundational assortment sciences and data products end-to-end, including documentation, CI / CD deployments, and input / output QA checks
• Identifying opportunities for standardization & automation of existing solutions and processes.
• Working closely with key internal stakeholders to ensure SLA's are met for model pipeline; output accuracy is consistent, reliable, and reproducible.
• Partner with other technical experts (i.e. engineering, architecture) to identify and implement best practices in tech stack, tool usage, and code development.

Qualifications, Skills, And Experience

Pay Transparency And Benefits

Pay Range : $97,000—$166,750 USD

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