Lead Data Scientist, Relevancy Sciences Data Science & Research – Personalization & Loyalty Strategy (P3764)

Relevancy Sciences Team is responsible for powering relevant, personalized, and scalable customer experiences across Kroger’s e-commerce ecosystem. We build and evolve the science behind search and recommendations that serve millions of customers and support high-scale digital experiences.

We are seeking a Lead Data Scientist to provide technical leadership across search and recommender systems, with a strong focus on modern model architectures, and production-ready machine learning. This role is ideal for someone who combines depth in applied machine learning with strong systems thinking, cross-functional influence, and contributes towards agentic capabilities.

What does the role entail? (Responsibilities)

Technical Leadership, Ownership, and Influence. Own and drive technical initiatives across search & recommender systems. Define and evolve the science strategy for improving content discovery, relevance, personalization, and decision support across digital experiences. Identify high-impact opportunities, make clear technical tradeoffs, and guide the team towards scalable, practical solutions. Rapidly prototype and validate new ideas to accelerate adoption and demonstrate measurable value.

Develop innovative search & recommender systems. Design and build ML solutions tailored to the unique needs of grocery retail domain. Lead the development of systems that improve product discovery and personalization across customer journeys. Bring strong technical and thought leadership on next generation personalization, including the use of Generative AI and agent-based approaches.

Evaluate and improve ML performance. Establish rigorous evaluation methodologies to assess the performance of ML systems across key metrics. Define robust online evaluation frameworks, and guide experimentation strategies that connect model improvements to customer and business outcomes.

Model serving and deployment. Partner closely with Engineering to build and deploy production-ready ML systems. Influence design decisions related to real-time inference, feature access, system integration, monitoring, and reliability. Ensure solutions meet latency, scalability, and operational requirements. Contribute to the evolution of serving and deployment strategies.

Cross-functional leadership. Work closely with Product, Engineering, and business stakeholders to translate needs into clear problem statements, hypotheses, and execution plans. Drive alignment across teams and influence decisions through clear communication of tradeoffs, risks, and expected outcomes.

Mentoring and knowledge sharing. Mentor data scientists and lead technical reviews to improve model quality, experimentation rigor, and systems thinking. Promote best practices in reproducibility and evaluation. Contribute to building a strong, learning-oriented team culture.

What skills and experience do you need? (Requirements)

• Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• 6+ years of experience applying machine learning to real-world problems with strong experience in search and recommender systems. Strong understanding of approaches such as embeddings and multi-stage decision systems.
• Strong proficiency in Python and SQL, with experience working on large-scale data using tools such as Spark.
• Experience with modern machine learning and deep learning frameworks such as PyTorch or TensorFlow.
• Strong foundation in statistics, experimentation, and data analysis, including design of experiments and A/B testing.
• Familiarity with large language models, foundation models, and emerging AI capabilities, including where they are applicable and where they are not.
• Experience evaluating or prototyping GenAI-based solutions is preferred.
• Experience partnering with engineering teams to deploy and maintain machine learning systems in production.
• Understanding of real-time systems, model serving, feature pipelines, and monitoring.
• Ability to make practical tradeoffs between model complexity, performance, latency, and scalability.
• Demonstrated ability to lead technical work across projects and influence direction across data science, engineering, and product teams.
• Experience mentoring or guiding other data scientists and contributing to a strong technical culture.
• Experience working with cloud platforms such as GCP or Azure.
• Experience in retail, e-commerce, or high-scale consumer domains is a plus.

Why join our team? (Rewards)

Impact millions of people. As a member of our data science team, you will have the opportunity to make a tangible difference in the lives of millions of customers by delivering relevant and personalized recommendations that enhance their grocery shopping experience. Your work will directly contribute to increasing customer satisfaction and loyalty, driving business outcomes for our company.

Continuous learning and development. Challenge yourself. We are committed to fostering a culture of continuous learning and development. You will have access to resources and support for expanding your knowledge and skills in cutting-edge technologies, including recommender systems, machine learning and artificial intelligence. Our team encourages exploration and experimentation, providing opportunities to stay at the forefront of industry advancements.

Work on new developments in recommender systems. Join a team at the forefront of innovation in recommender systems and AI. You will have the chance to contribute to pushing the boundaries of what’s possible in personalized recommendation technology. You will have the chance to work on exciting projects that leverage the latest developments in deep learning architectures and data science methodologies.

#LI-SSS

Job Summary 

PatientPoint is seeking a strategic and hands-on Director, Content Strategy & Activation to build and lead our newly established Content Marketing Center of Excellence. 

This role sits at the intersection of enterprise storytelling, campaign activation, AI-enabled content scaling and measurable business impact. You will architect and operationalize a comprehensive content strategy that supports multiple business units, aligns to enterprise priorities and drives engagement, affinity, demand and retention across our audiences. 

You will manage and mentor a team of content marketers while personally contributing to high-impact content development and campaign integration. This leader must be both a visionary strategist and an execution-oriented operator — someone who can define the roadmap and ensure content delivers measurable business results. 

What You’ll Do  

Enterprise Content Strategy & Narrative Leadership 

• Develop and lead a comprehensive enterprise content strategy aligned to PatientPoint’s brand, growth priorities and revenue goals 

• Build and evolve core narrative frameworks that articulate PatientPoint’s value across providers, life sciences partners, customers and enterprise stakeholders 

• Ensure content strategies reflect distinct buyer journeys, target audiences, value propositions and selling points across business units 

• Identify opportunities to leverage synergies across segments while maintaining audience relevance 

• Continuously monitor shifts in the healthcare, digital health, media and marketing landscape to ensure our content remains credible, differentiated and forward-looking 

Campaign Strategy & Content Activation 

• Partner closely with segment marketing directors to translate campaign strategies into cohesive, multi-channel content plans 

• Ensure campaigns are grounded in strong storytelling and connected to broader enterprise narratives 

• Own campaign content strategy and execution — from concept through deployment 

Owned Media & Content Ecosystem Management 

• Own and evolve PatientPoint’s owned media ecosystem, including website, blog, newsletters and other avenues in which you see opportunity  

• Architect an editorial roadmap aligned to strategic priorities and campaign focus areas 

• Implement a scalable “content atomization” model that repurposes cornerstone assets (research, webinars, case studies) into high-impact derivative content 

• Embed SEO and emerging AI visibility best practices into the content lifecycle to ensure discoverability and authority 

Thought Leadership & Market-Relevant Content 

• Proactively monitor healthcare, digital health, media, policy and marketing industry trends to identify timely opportunities for PatientPoint to contribute a differentiated perspective 

• Rapidly translate breaking news, emerging research, regulatory shifts and cultural moments into relevant, high-quality content that positions PatientPoint at the center of industry conversations 

• Develop clear POV-driven content that articulates PatientPoint’s unique stance on topics impacting providers, patients and life sciences partners 

• Partner cross-functionally to surface frontline insights, customer perspectives and proprietary data that strengthen our authority and credibility 

• Ensure thought leadership content is timely, distinctive and aligned to enterprise priorities while reinforcing our long-term narrative 

• Leverage multiple channels — including blog, social, email, PR collaboration and sales enablement — to amplify our voice in key industry discussions 

Measurement, Analytics & Optimization 

• Establish and lead a robust content analytics and reporting framework 

• Define KPIs tied to engagement, campaign performance, customer engagement and sales enablement effectiveness 

• Translate performance data into actionable insights to refine messaging, formats and distribution strategies 

• Continuously optimize based on business priorities and measurable impact 

Team Leadership & Cross-Functional Collaboration 

• Manage and mentor a team of content marketing managers, setting clear expectations and elevating quality standards 

• Foster a culture of craft, accountability and innovation within the content function 

• Partner cross-functionally with Product, Brand, Demand, Customer Marketing, Sales, Content, Data & Insights, Corp Comms and Customer Success to ensure alignment and consistency 

• Serve as the connective tissue between strategy and execution — ensuring ideas translate into high-quality, business-driving assets 

What We Need 

• 10+ years of progressive experience in content strategy, campaign marketing, or editorial leadership within B2B healthcare, digital health, media or technology environments 

• Demonstrated experience building and scaling content programs across multiple audiences or business units 

• Proven ability to operate at both strategic and hands-on levels 

• Experience leading and developing high-performing creative or content teams 

• Strong editorial judgment and exceptional writing and storytelling skills 

• Experience integrating content into demand generation and campaign strategies 

• Proficiency with marketing technology platforms, CMS, analytics tools, marketing automation systems, SEO tools and generative AI platforms 

• Ability to translate complex healthcare and technology concepts into clear, compelling narratives 

• Bachelor’s degree in Marketing, Communications, Journalism or related field 

• Agency experience preferred  

What You’ll Need to Succeed 

• A clearly defined and operational Content Marketing Center of Excellence 

• Cohesive, enterprise-aligned narrative frameworks – messaging guides, personas, buyer journeys – across business units 

• Campaigns activated through strategic, high-performing content 

• Increased content efficiency and output through AI-enabled workflows 

• Measurable impact on engagement, campaign performance and customer engagement 

• Elevated executive and thought leadership presence in the healthcare ecosystem 

Senior Data Scientist / P3358

Summary

We are seeking a Senior Data Scientist to join our Proprietary Models team. In this role, you will play a critical part in developing, evaluating, and democratizing our foundation models portfolio—including embeddings, pre-trained LLMs, and fine-tuned language models. You will build and optimize embedding pipelines, design rigorous evaluation frameworks, drive models from experimentation to production, and guide business stakeholders through the process of integrating these models into their workflows. The ideal candidate combines deep technical expertise in machine learning and AI with strong problem-solving abilities, a commitment to engineering excellence, and a passion for enabling others to leverage AI effectively.

Responsibilities

Your work will cover a lot of ground, from engineering data pipelines to testing novel AI methodologies to guiding business stakeholders. You will be expected to flex between these skill domains as work progresses through its lifecycle, and to collaborate within a team to make it all happen.

• Develop and optimize embedding pipelines for vector search, retrieval-augmented generation (RAG), and downstream ML applications.
• Conduct rigorous model testing, evaluation, and validation against quality metrics, performance benchmarks, and reliability standards prior to release.
• Design and execute proof of concepts to demonstrate feasibility for specific business problems.
• Build and maintain automated testing frameworks for model performance, data quality, and pipeline integrity.
• Collaborate with MLE/Researchers/Engineers to develop, fine-tune, and deploy foundation models.
• Perform exploratory data analysis (EDA), feature engineering, and data preprocessing to support model development.
• Develop and maintain Jupyter notebooks, scripts, and workflows for reproducible experimentation and analysis.
• Contribute to building and maintenance of code packages, APIs, hosted applications, and other foundation model delivery mechanisms.
• Troubleshoot integration challenges and provide technical guidance for model integrations.
• Guide business stakeholders, data science and engineering teams through adoption and integration of foundation embedding and generative AI models.
• Create documentation, user guides, and best practices for internal model adoption and usage.
• Serve as a liaison between the Foundation Models team and business stakeholders, gathering feedback to inform the development roadmap.

Qualifications and Experience

Required

• Bachelor’s degree in Data Science, ML, Computer Science, or a related discipline
• 3+ years of hands-on experience in data science or machine learning roles
• 3+ years’ experience building in Python using big data tools (e.g. Hadoop, Databricks)
• Hands-on experience building processes incorporating LLMs, embeddings, or related model architecture
• Experience applying embeddings within AI projects and machine learning applications
• Track record of shipping, measuring, and maintaining machine learning models in production
• Exceptional communication skills with ability to explain complex technical concepts to non-technical audiences
• Experience in stakeholder management, technical documentation creation, and cross-functional collaboration

Preferred

• Experience building in cloud data platforms (i.e. Azure, GCP)
• Previous developer relations, technical evangelism, or advocacy experience
• Background in NLP, conversational AI, or generative AI applications
• Open-source contributions or thought leadership in AI/ML community

#LI-SSS

Lead Technical Product Manager(G3) 

LOCATION: Chicago/Cincinnati 

COMPANY OVERVIEW: 

84.51° knows customers, and we know how to connect you.  

Using a sophisticated, proprietary suite of tools and technology, we turn customer data into actionable knowledge. With unparalleled customer data and predictive analytics capabilities, we deliver personalized marketing strategies and ensure the best experience for customers of Kroger and more than 300 consumer-packaged-goods companies. We put the customer at the center of everything we do, resulting in a more dynamic, informed and personal approach to driving customer loyalty. 

SUMMARY:  

The AI Enablement team builds foundational AI capabilities that transform Kroger and 84.51, including better solutions and outcomes for our shoppers and our associates. AI Gateway is a cross-functional team within AI Enablement responsible for the primary AI model and API infrastructure that powers these solutions and democratizes access to AI across the org. As the Product Manager for this team, you will work closely with the Director of Product, Tech Leads for the AI Gateway, and cross-functional design and development teams. 

The LEAD PRODUCT MANAGER is the chief navigator, business champion, and team linguist that is accountable for setting team priorities and maximizing the value of the product results from the work of the development team. You own the details of the business and technical value delivered at the team level. You translate business requirements into product requirements to ensure that the product delivers on user needs. You own the measurement of the value delivered and other metrics for your product. This role requires excellent organizational and communication skills, technical acumen, and artificial intelligence domain knowledge. 

RESPONSIBILITIES:  

• Drive business value for the team by prioritizing and ordering product backlog items based on the product roadmap, inclusive of product, engineering, UX and data science roadmaps. 
• Experienced in managing multiple teams’ product backlogs in parallel and ensuring they’re transparent, visible and clearly communicated.
• Partner with cross-functional engineering, UX and data science peers to translate business desires/requirements into effective features and stories that are ready for development.
• Outlines clear acceptance criteria, to clearly communicate the definition of “done”.
• Partner with external contractors or technical support to ensure the delivery of the scope of work, within the agreed timeline, and in accordance to the stated acceptance criteria.
• Deep understanding of the business domain, stakeholders, business processes and constraints in which your product(s) play 
• Deep understanding of customers/users’ problems, how they think and operate and the platforms/technology they use. Ability to become familiar with new technology, business domains, and/or analytical practices that impact your product(s). 
• Understand and communicate organization objectives, strategies and solution needs to the team to facilitate results (where collaborative/as colleague)
• Manage and communicate dependencies and risks.
• Stakeholder management – experienced in building and managing internal and external stakeholder relationships to influence and drive change.
• Experienced level knowledge in the development and use of product data to influence product decisions/roadmap – both quantitative and qualitative.
• Clearly communicate the value of the work being delivered

QUALIFICATIONS, SKILLS, AND EXPERIENCE:  

• Professional work experience in artificial intelligence / Generative AI applications.
• Experience managing and/or developing an API-based product or developer tooling.
• Experience managing and/or developing cloud-based solutions in Azure or Google Cloud.
• Experience scaling apps or systems to meet high-availability and resiliency requirements for critical internal and customer facing solutions.
  • Experience managing and/or working on a team that deploys AI/ML models in cloud-based settings.
  • Technical acumen – possess the foundational technical knowledge needed to communicate with the technical team, understand blockers/trade-offs, and incorporate technical needs in the roadmap.
  • Experience navigating corporate governance processes including Security, Cloud, Privacy, Data Sharing, and Legal.
• Skilled in managing cross-functional software development teams in an agile environment
• Skilled in managing business priorities against design/user needs while delivering against product roadmaps
• Skilled in managing end-to-end software product development.
• Stakeholder management skills – experienced in building and managing stakeholder relationships to influence and drive change.
• Problem solving, critical thinking and analytical skills
• Planning, organizational and time management skills
• Comfort with ambiguity – remains confident, positive and resourceful in the face of ambiguity and unexpected results; recovers quickly from setbacks.
• Exhibits qualities of and have proven to be a great teammate
• Verbal and written communication skills, ability to translate between business and technical
• 4-6 years relevant experience
• Education: Bachelor’s degree or equivalent experience

ADDITIONAL SKILLS OF INTEREST (NOT REQUIRED) 

• Prior experience as a software engineer or Technical Product Manager – many of our customers are software engineers and data scientists.
• Experience leveraging various Generative AI chat tools (ie M365 Copilot, ChatGPT, Gemini, Claude) to simplify your life, work, or otherwise automate processes and accomplish previously impossible things. 
• Experience developing AI Agents using an agent builder or agent framework.
• Experience developing or using MCP servers.
• Experience using coding agents (ie Claude Code, Codex, Gemini CLI, Github Copilot).