Senior Data Scientist Consultant - Agentic Platform; P4339

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.

The Agent Platform Team, within AI Enablement °, owns and manages the core platforms that power data science and AI across the organization. This role sits on the SPI (Science Platform Innovation) squad and is focused specifically on the Databricks environment and its evolving AI/ML capabilities. You will be the bridge between the engineers building and maintaining our Databricks platform and the data scientists who use it every day.

You are not building models for end‑clients; instead you ensure the platform behaves as expected for the people on it, that new capabilities are tested, documented and adopted smoothly, and that practitioner pain points are sent back to the platform team in a way that shapes the roadmap.

You’ll build deep familiarity with Databricks’ infrastructure and AI powered capabilities—including Genie Code, Genie spaces, Agent Bricks, MLflow and other features as they emerge—as well as the Unity Catalog governance layer that underpins them. You’ll test and evaluate new Databricks features and relevant third‑party integrations from the perspective of an end‑user, document your findings, and help the team decide what to adopt, how to roll it out and what to skip.

This is a small, highly collaborative squad. Everyone pitches in on a bit of everything. Priorities shift frequently as the Databricks roadmap evolves. Success in this role is less about fixed technical expertise and more about comfort with ambiguity, good judgment about where to spend your time and the ability to influence without direct authority.

• Voice of the practitioner:
  Serve as the primary liaison between data scientists using Databricks and the platform engineering team, gather requirements, surface pain points and translate practitioner needs into actionable feedback that shapes platform decisions and roadmaps.
• Technology evaluation:
  Lead the testing and evaluation of new Databricks capabilities (e.g., Mosaic AI features, Model Serving enhancements, Genie, new Unity Catalog functionality) and relevant third‑party tools. Document findings, recommended use cases, limitations and rollout considerations.
• Onboarding & enablement:
  Write guides, maintain documentation, lead training sessions and run office hours to help data scientists adopt new platform capabilities. Partner with Learning & Development where appropriate and serve as a first line of support when teams hit roadblocks.
• Adoption & communication:
  Evangelize Databricks capabilities to increase awareness and drive adoption. Produce clear release notes, communications and materials for both technical and non‑technical audiences.
• Cross‑functional collaboration:
  Work closely with the solution architect, cloud engineer and product senior on the squad to ensure proposed technologies have well‑defined use cases and that guidelines and best practices are established. Act as a data science ambassador to cross‑functional teams, explaining recommended workflows and the reasoning behind platform choices.
• Governance & compliance support:
  Help validate that new platform capabilities meet enterprise requirements around security, compliance, observability and data governance (e.g., Unity Catalog lineage, Azure connectivity).

• Bachelor’s degree in mathematics, statistics, computer science, economics or a related discipline.
• 2–4 years of experience in data science, AI/ML development or applied…