Qureos Mentor

84.51°

<div><div>84.51&deg; Overview:

84.51&deg; 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&deg; Insights, 84.51&deg; Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.

84.51&deg; follows a 5‑day in‑office work schedule to support collaboration, alignment, and team connection.

Join us at 84.51&deg;!

__________________________________________________________</div><div> 
Lead Product Manager &ndash; Forecasting Center of Excellence P4373
The Forecasting Center of Excellence (FCOE) at 84.51&deg; delivers accurate, timely sales forecasts that empower decision-makers at Kroger, 84.51&deg;, and our CPG partners. Our forecasts fuel better insights, optimized operations, and strategic business decisions.

As a Lead Product Manager, you'll drive day-to-day delivery and medium term strategic direction for forecasting products. You'll translate business needs into clear, prioritized work, own the near-term product roadmap, and collaborate closely with engineering and data science teams to ensure timely, high-quality delivery. You&rsquo;ll influence stakeholders, guide strategic decisions, and mentor junior team members to ensure product success.

This role reports directly to the Product Director of FCOE.

Responsibilities:

Product Roadmap and Business Ownership
<ul>
<li>Own and maintain the product roadmap (0-12 months), clearly aligning work priorities with user needs, business objectives, and strategic initiatives.</li>
<li>Develop clear measures of success focused on user value, tracking and communicating outcomes regularly to stakeholders.</li>
</ul>
Product Delivery and Technical Collaboration
<ul>
<li>Actively lead sprint planning, clearly defining user stories, acceptance criteria, and prioritization frameworks for forecasting products.</li>
<li>Collaborate closely with Engineering and Data Science partners to ensure technical feasibility, remove obstacles, and deliver timely, impactful solutions.</li>
<li>Own product backlog management, including writing clear, detailed user stories and managing initiatives through completion.</li>
</ul>
Communication and Stakeholder Alignment
<ul>
<li>Serve as a cross-functional and cross-team connector, proactively identifying and managing critical touchpoints.</li>
<li>Clearly communicate product goals, progress, and value, influencing leaders and stakeholders to align around strategic priorities.</li>
</ul>
Strategic Influence and Thought Leadership
<ul>
<li>Continuously inform product strategy by identifying emerging opportunities or risks, influencing senior stakeholders to maximize product value.</li>
<li>Proactively suggest improvements to team practices, processes, and approaches, using feedback, data, and market insights to drive innovation.</li>
</ul>
Mentorship and Functional Leadership
<ul>
<li>Actively coach and mentor junior team members (Product Managers, Associate PMs), supporting their growth and improving team performance.</li>
<li>Contribute functional expertise within the broader organization, acting as a resource and informal leader for best practices in product management.</li>
</ul>
Qualifications, Skills, and Experience:
<ul>
<li>5+ years of product management experience, ideally focused on data-intensive, analytical, or technical products.</li>
<li>Proven ability to autonomously manage complex product roadmaps, balancing competing priorities and delivering measurable outcomes.</li>
<li>Excellent communication and influencing skills, capable of clearly articulating technical information and business value to diverse stakeholders.</li>
<li>Demonstrated proficiency in agile methodologies, including writing user stories, defining acceptance criteria, and prioritizing work effectively.</li>
<li>Experience collaborating closely with technical teams (Engineering/Data Science), ensuring mutual clarity and timely execution.</li>
<li>Experience with product management software. Our tech stack is Github, Jira, and Shibumi and experience here is a plus, but not required.</li>
<li>Familiarity with forecasting, data science, or analytics products is strongly preferred; retail/grocery experience is a plus.</li>
<li>Bachelor&rsquo;s degree or equivalent experience in data science, computer science, engineering, mathematics, or related fields</li></ul> 


#LI-EB1</div><div><div><div><div>
Pay Transparency and Benefits
<ul>
<li>The stated salary range represents the entire span applicable across all geographic markets from lowest to highest. Actual salary offers will be determined by multiple factors including but not limited to geographic location, relevant experience, knowledge, skills, other job-related qualifications, and alignment with market data and cost of labor. In addition to salary, this position is also eligible for variable compensation.</li>
<li>Below is a list of some of the benefits we offer our associates:
</li><li><ul><li>Health: Medical: with competitive plan designs and support for self-care, wellness and mental health. Dental: with in-network and out-of-network benefit. Vision: with in-network and out-of-network benefit.</li>
<li>Wealth: 401(k) with Roth option and matching contribution. Health Savings Account with matching contribution (requires participation in qualifying medical plan). AD&amp;D and supplemental insurance options to help ensure additional protection for you.</li>
<li>Happiness: Paid time off with flexibility to meet your life needs, including 5 weeks of vacation time, 7 health and wellness days, 3 floating holidays, as well as 6 company-paid holidays per year. Paid leave for maternity, paternity and family care instances.</li> 
</ul></li>
</ul></div></div>Pay Range
$125,000 - $172,500 USD</div></div></div>

Lead Product Manager – Forecasting Center of Excellence (P4373) New

<div><div>84.51&deg; Overview:

84.51&deg; 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&deg; Insights, 84.51&deg; Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.

84.51&deg; follows a 5‑day in‑office work schedule to support collaboration, alignment, and team connection.

Join us at 84.51&deg;!

__________________________________________________________</div> 
Lead Product Manager &ndash; Forecasting Center of Excellence P4373
The Forecasting Center of Excellence (FCOE) at 84.51&deg; delivers accurate, timely sales forecasts that empower decision-makers at Kroger, 84.51&deg;, and our CPG partners. Our forecasts fuel better insights, optimized operations, and strategic business decisions.

As a Lead Product Manager, you'll drive day-to-day delivery and medium term strategic direction for forecasting products. You'll translate business needs into clear, prioritized work, own the near-term product roadmap, and collaborate closely with engineering and data science teams to ensure timely, high-quality delivery. You'll influence stakeholders, guide strategic decisions, and mentor junior team members to ensure product success.

This role reports directly to the Product Director of FCOE.

Responsibilities:

Product Roadmap and Business Ownership
<ul>
<li>Own and maintain the product roadmap (0-12 months), clearly aligning work priorities with user needs, business objectives, and strategic initiatives.</li>
<li>Develop clear measures of success focused on user value, tracking and communicating outcomes regularly to stakeholders.</li>
</ul>
Product Delivery and Technical Collaboration
<ul>
<li>Actively lead sprint planning, clearly defining user stories, acceptance criteria, and prioritization frameworks for forecasting products.</li>
<li>Collaborate closely with Engineering and Data Science partners to ensure technical feasibility, remove obstacles, and deliver timely, impactful solutions.</li>
<li>Own product backlog management, including writing clear, detailed user stories and managing initiatives through completion.</li>
</ul>
Communication and Stakeholder Alignment
<ul>
<li>Serve as a cross-functional and cross-team connector, proactively identifying and managing critical touchpoints.</li>
<li>Clearly communicate product goals, progress, and value, influencing leaders and stakeholders to align around strategic priorities.</li>
</ul>
Strategic Influence and Thought Leadership
<ul>
<li>Continuously inform product strategy by identifying emerging opportunities or risks, influencing senior stakeholders to maximize product value.</li>
<li>Proactively suggest improvements to team practices, processes, and approaches, using feedback, data, and market insights to drive innovation.</li>
</ul>
Mentorship and Functional Leadership
<ul>
<li>Actively coach and mentor junior team members (Product Managers, Associate PMs), supporting their growth and improving team performance.</li>
<li>Contribute functional expertise within the broader organization, acting as a resource and informal leader for best practices in product management.</li>
</ul>
Qualifications, Skills, and Experience:
<ul>
<li>5+ years of product management experience, ideally focused on data-intensive, analytical, or technical products.</li>
<li>Proven ability to autonomously manage complex product roadmaps, balancing competing priorities and delivering measurable outcomes.</li>
<li>Excellent communication and influencing skills, capable of clearly articulating technical information and business value to diverse stakeholders.</li>
<li>Demonstrated proficiency in agile methodologies, including writing user stories, defining acceptance criteria, and prioritizing work effectively.</li>
<li>Experience collaborating closely with technical teams (Engineering/Data Science), ensuring mutual clarity and timely execution.</li>
<li>Experience with product management software. Our tech stack is Github, Jira, and Shibumi and experience here is a plus, but not required.</li>
<li>Familiarity with forecasting, data science, or analytics products is strongly preferred; retail/grocery experience is a plus.</li>
<li>Bachelor's degree or equivalent experience in data science, computer science, engineering, mathematics, or related fields</li></ul> 


#LI-EB1</div>

Lead Product Manager – Forecasting Center of Excellence (P4373)

<div><div>84.51&deg; Overview:

84.51&deg; 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&deg; Insights, 84.51&deg; Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.

84.51&deg; follows a 5‑day in‑office work schedule to support collaboration, alignment, and team connection.

Join us at 84.51&deg;!

__________________________________________________________</div><div> 
Lead API Platform Engineer (Cincinnati / Chicago) P181
<h1 class="jobSectionHeader">
About 84.51&deg;</h1>

84.51&deg; is a data science and technology company (owned by Kroger) that turns customer data into decisions that improve how people shop. Engineers here work with modern cloud and data tech at meaningful scale, alongside product, data science, and business teams.
<h1 class="jobSectionHeader">
The role</h1>

We&rsquo;re hiring a Lead API Platform Engineer to join our Application Delivery team within Platform Engineering. This is an individual contributor (IC) technical lead role, owning the API gateway experience end-to-end &mdash; from pre-production through production. You&rsquo;ll help shape technical direction, mentor engineers, and continuously improve our on-call/escalation rotation &mdash; participating and fielding gateway-related production issues when on rotation. 

If you meet most&mdash;but not all&mdash;requirements, we still encourage you to apply.
<h1 class="jobSectionHeader">
What you&rsquo;ll do</h1>
<ul><li>Own our gateway platforms: Maintain and evolve our Kong Enterprise API Gateway and Azure Application Gateway configurations, standards, and best practices&mdash;and help design what&rsquo;s next.</li>
<li>Strengthen API security: Implement and promote API security standards, including OAuth2, JWT, and SAML, along with access controls and encryption.</li>
<li>Improve reliability and performance: Monitor, troubleshoot, and optimize using Datadog. Tune latency, caching behavior, and rate limiting to support high-performing APIs.</li>
<li>Automate delivery: Build and maintain automation and CI/CD workflows (using GitHub Actions) for gateway deployments and policy/configuration updates.</li>
<li>Enable great developer experience: Improve how teams build and test APIs by standardizing gateway onboarding, providing self-service patterns, and supporting reliable local development workflows (e.g., local gateway tooling, mock/test routes, and clear &ldquo;run it locally&rdquo; docs).</li>
<li>Shape work for success: define and decompose scope into ready-to-build requirements (clear user stories and acceptance criteria), aligning on delivery standards, and proactively removing blockers to keep execution on track.</li>
<li>Support production operations: Provide L2/L3 support, participate in an on-call rotation, lead root-cause analysis, and drive permanent fixes.</li>
<li>Collaborate and document: Partner with development, QA, security, and architecture teams. Create clear documentation, SOPs, and onboarding materials to help teams ship confidently.</li>
</ul><h1 class="jobSectionHeader">What we&rsquo;re looking for</h1>
<ul><li>Bachelor&rsquo;s degree (Master&rsquo;s degree desired) typically in Computer Science, Management Information Systems, Mathematics, Business Analytics or another technically strong program.</li>
<li>5+ years of hands-on experience operating API gateways in production environments (especially Kong)</li>
<li>Strong API fundamentals (REST, JSON) and security best practices</li>
<li>Experience working in a public cloud environment, plus solid networking knowledge (DNS, firewalls, load balancers) &ndash; Azure preferred but not required</li>
<li>Comfort scripting and/or coding in one or more languages (e.g., Python, Shell, Java, Node.js)</li>
<li>Familiarity with DevOps/Agile practices, Docker/Kubernetes/Helm, and Terraform (or other IaC tools)</li>
<li>Clear communication skills and a collaborative mindset in a fast-moving environment</li></ul> 


#LI-SSS</div><div><div><div><div> 
Pay Transparency and Benefits
<ul>
<li>The stated salary range represents the entire span applicable across all geographic markets from lowest to highest. Actual salary offers will be determined by multiple factors including but not limited to geographic location, relevant experience, knowledge, skills, other job-related qualifications, and alignment with market data and cost of labor. In addition to salary, this position is also eligible for variable compensation.</li>
<li>Below is a list of some of the benefits we offer our associates:
</li><li><ul><li>Health: Medical: with competitive plan designs and support for self-care, wellness and mental health. Dental: with in-network and out-of-network benefit. Vision: with in-network and out-of-network benefit.</li>
<li>Wealth: 401(k) with Roth option and matching contribution. Health Savings Account with matching contribution (requires participation in qualifying medical plan). AD&amp;D and supplemental insurance options to help ensure additional protection for you.</li>
<li>Happiness: Paid time off with flexibility to meet your life needs, including 5 weeks of vacation time, 7 health and wellness days, 3 floating holidays, as well as 6 company-paid holidays per year. Paid leave for maternity, paternity and family care instances.</li> 
</ul></li>
</ul></div></div>Pay Range
$125,000 - $207,000 USD</div></div></div>

Lead API Platform Engineer (P181) New

<div><div>84.51&deg; Overview:

84.51&deg; 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&deg; Insights, 84.51&deg; Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.

84.51&deg; follows a 5‑day in‑office work schedule to support collaboration, alignment, and team connection.

Join us at 84.51&deg;!

__________________________________________________________</div><div><h1 class="jobSectionHeader"> 
Senior Data Scientist Consultant, SPI &ndash; Agent Platform Team</h1>
<h2 class="jobSectionHeader">Summary</h2>

The Agent Platform Team, within AI Enablement at 84.51&deg;, 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&mdash;that new capabilities are tested, documented, and adopted smoothly, and that practitioner pain points make it back to the platform team in a way that shapes the roadmap.

You&rsquo;ll build deep familiarity with Databricks&rsquo; infrastructure and AI powered capabilities &mdash;including Genie Code, Genie spaces, Agent Bricks, MLflow, and other features as they emerge&mdash;as well as the Unity Catalog governance layer that underpins them. You&rsquo;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.
<h2 class="jobSectionHeader">
Responsibilities</h2>
<ul><li>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.</li>
<li>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. Over time, this may evolve from hands-on beta testing toward designing and coordinating evaluation efforts across groups of practitioners.</li>
<li>Onboarding &amp; enablement: Write guides, maintain documentation, lead training sessions, and run office hours to help data scientists adopt new platform capabilities. Partner with Learning &amp; Development where appropriate. Serve as a first line of support when teams hit roadblocks.</li>
<li>Adoption &amp; communication: Evangelize Databricks capabilities to increase awareness and drive adoption. Produce clear release notes, communications, and materials for both technical and non-technical audiences.</li>
<li>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.</li>
<li>Governance &amp; 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).</li>
</ul><h2 class="jobSectionHeader">Qualifications &amp; Experience</h2>
<ul><li>Bachelor&rsquo;s degree in mathematics, statistics, computer science, economics, or a related discipline.</li>
<li>2&ndash;4 years of experience in data science, AI/ML development, or applied analytics.</li>
<li>2&ndash;4 years of experience in tech consulting, retail analytics, or related professional services.</li>
<li>Hands-on experience with Python, SQL, and PySpark.</li>
<li>Experience gathering user needs, documenting requirements, and driving issues to resolution with technical teams.</li>
<li>Experience partnering with software engineering and/or product management teams.</li>
<li>Familiarity with LLMs, prompt engineering, or agentic AI concepts is a strong plus.</li>
<li>Experience with the Databricks ecosystem (Unity Catalog, MLflow) is a strong plus.</li>
<li>Exposure to agent frameworks (e.g., LangChain, LangGraph, CrewAI, AutoGen) is a plus.</li>
</ul><h2 class="jobSectionHeader">Skills</h2>
<ul><li>Strong written and verbal communication, including the ability to explain technical concepts clearly to non-technical audiences and produce high-quality documentation.</li>
<li>Ability to influence across teams and seniority levels without direct authority.</li>
<li>Comfort operating in ambiguity&mdash;priorities shift frequently, and you need good instincts about where to focus.</li>
<li>Strong project and time management skills; able to manage multiple priorities with minimal oversight.</li>
<li>Curiosity and enthusiasm for emerging AI technologies and a genuine desire to become a subject matter expert on the Databricks platform and its AI capabilities.</li></ul> 


#LI-SSS</div><div><div><div><div>
Pay Transparency and Benefits
<ul>
<li>The stated salary range represents the entire span applicable across all geographic markets from lowest to highest. Actual salary offers will be determined by multiple factors including but not limited to geographic location, relevant experience, knowledge, skills, other job-related qualifications, and alignment with market data and cost of labor. In addition to salary, this position is also eligible for variable compensation.</li>
<li>Below is a list of some of the benefits we offer our associates:
</li><li><ul><li>Health: Medical: with competitive plan designs and support for self-care, wellness and mental health. Dental: with in-network and out-of-network benefit. Vision: with in-network and out-of-network benefit.</li>
<li>Wealth: 401(k) with Roth option and matching contribution. Health Savings Account with matching contribution (requires participation in qualifying medical plan). AD&amp;D and supplemental insurance options to help ensure additional protection for you.</li>
<li>Happiness: Paid time off with flexibility to meet your life needs, including 5 weeks of vacation time, 7 health and wellness days, 3 floating holidays, as well as 6 company-paid holidays per year. Paid leave for maternity, paternity and family care instances.</li> 
</ul></li>
</ul></div></div>Pay Range
$98,000 - $169,050 USD</div></div></div>

Senior Data Scientist Consultant - Agentic Platform (P2393) New

<div><div>84.51&deg; Overview:

84.51&deg; 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&deg; Insights, 84.51&deg; Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.

84.51&deg; follows a 5‑day in‑office work schedule to support collaboration, alignment, and team connection.

Join us at 84.51&deg;!

__________________________________________________________</div><h1 class="jobSectionHeader"> 
Senior Data Scientist Consultant, SPI &ndash; Agent Platform Team</h1>
<h2 class="jobSectionHeader">Summary</h2>

The Agent Platform Team, within AI Enablement at 84.51&deg;, 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&mdash;that new capabilities are tested, documented, and adopted smoothly, and that practitioner pain points make it back to the platform team in a way that shapes the roadmap.

You'll build deep familiarity with Databricks' infrastructure and AI powered capabilities &mdash;including Genie Code, Genie spaces, Agent Bricks, MLflow, and other features as they emerge&mdash;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.
<h2 class="jobSectionHeader">
Responsibilities</h2>
<ul><li>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.</li>
<li>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. Over time, this may evolve from hands-on beta testing toward designing and coordinating evaluation efforts across groups of practitioners.</li>
<li>Onboarding &amp; enablement: Write guides, maintain documentation, lead training sessions, and run office hours to help data scientists adopt new platform capabilities. Partner with Learning &amp; Development where appropriate. Serve as a first line of support when teams hit roadblocks.</li>
<li>Adoption &amp; communication: Evangelize Databricks capabilities to increase awareness and drive adoption. Produce clear release notes, communications, and materials for both technical and non-technical audiences.</li>
<li>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.</li>
<li>Governance &amp; 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).</li>
</ul><h2 class="jobSectionHeader">Qualifications &amp; Experience</h2>
<ul><li>Bachelor's degree in mathematics, statistics, computer science, economics, or a related discipline.</li>
<li>2&ndash;4 years of experience in data science, AI/ML development, or applied analytics.</li>
<li>2&ndash;4 years of experience in tech consulting, retail analytics, or related professional services.</li>
<li>Hands-on experience with Python, SQL, and PySpark.</li>
<li>Experience gathering user needs, documenting requirements, and driving issues to resolution with technical teams.</li>
<li>Experience partnering with software engineering and/or product management teams.</li>
<li>Familiarity with LLMs, prompt engineering, or agentic AI concepts is a strong plus.</li>
<li>Experience with the Databricks ecosystem (Unity Catalog, MLflow) is a strong plus.</li>
<li>Exposure to agent frameworks (e.g., LangChain, LangGraph, CrewAI, AutoGen) is a plus.</li>
</ul><h2 class="jobSectionHeader">Skills</h2>
<ul><li>Strong written and verbal communication, including the ability to explain technical concepts clearly to non-technical audiences and produce high-quality documentation.</li>
<li>Ability to influence across teams and seniority levels without direct authority.</li>
<li>Comfort operating in ambiguity&mdash;priorities shift frequently, and you need good instincts about where to focus.</li>
<li>Strong project and time management skills; able to manage multiple priorities with minimal oversight.</li>
<li>Curiosity and enthusiasm for emerging AI technologies and a genuine desire to become a subject matter expert on the Databricks platform and its AI capabilities.</li></ul> 


#LI-SSS</div>

Senior Data Scientist Consultant - Agentic Platform (P2393)

<div><div>84.51&deg; Overview:

84.51&deg; 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&deg; Insights, 84.51&deg; Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.

84.51&deg; follows a 5‑day in‑office work schedule to support collaboration, alignment, and team connection.

Join us at 84.51&deg;!

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

Required
<ul>
<li>Bachelor's degree in Data Science, ML, Computer Science, or a related discipline</li>
<li>3+ years of hands-on experience in data science or machine learning roles</li>
<li>3+ years' experience building in Python using big data tools (e.g. Hadoop, Databricks)</li>
<li>Hands-on experience building processes incorporating LLMs, embeddings, or related model architecture</li>
<li>Experience applying embeddings within AI projects and machine learning applications</li>
<li>Track record of shipping, measuring, and maintaining machine learning models in production</li>
<li>Exceptional communication skills with ability to explain complex technical concepts to non-technical audiences</li>
<li>Experience in stakeholder management, technical documentation creation, and cross-functional collaboration</li>
</ul>
Preferred
<ul>
<li>Experience building in cloud data platforms (i.e. Azure, GCP)</li>
<li>Previous developer relations, technical evangelism, or advocacy experience</li>
<li>Background in NLP, conversational AI, or generative AI applications</li>
<li>Open-source contributions or thought leadership in AI/ML community</li>
</ul>
#LI-SSS</div>

Senior Data Scientist (P3358)

<div><div>84.51&deg; Overview:

84.51&deg; 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&deg; Insights, 84.51&deg; Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.

84.51&deg; follows a 5‑day in‑office work schedule to support collaboration, alignment, and team connection.

Join us at 84.51&deg;!

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

Required
<ul>
<li>Bachelor&rsquo;s degree in Data Science, ML, Computer Science, or a related discipline</li>
<li>3+ years of hands-on experience in data science or machine learning roles</li>
<li>3+ years&rsquo; experience building in Python using big data tools (e.g. Hadoop, Databricks)</li>
<li>Hands-on experience building processes incorporating LLMs, embeddings, or related model architecture</li>
<li>Experience applying embeddings within AI projects and machine learning applications</li>
<li>Track record of shipping, measuring, and maintaining machine learning models in production</li>
<li>Exceptional communication skills with ability to explain complex technical concepts to non-technical audiences</li>
<li>Experience in stakeholder management, technical documentation creation, and cross-functional collaboration</li>
</ul>
Preferred
<ul>
<li>Experience building in cloud data platforms (i.e. Azure, GCP)</li>
<li>Previous developer relations, technical evangelism, or advocacy experience</li>
<li>Background in NLP, conversational AI, or generative AI applications</li>
<li>Open-source contributions or thought leadership in AI/ML community</li>
</ul>
#LI-SSS</div><div><div><div><div> 
Pay Transparency and Benefits
<ul>
<li>The stated salary range represents the entire span applicable across all geographic markets from lowest to highest. Actual salary offers will be determined by multiple factors including but not limited to geographic location, relevant experience, knowledge, skills, other job-related qualifications, and alignment with market data and cost of labor. In addition to salary, this position is also eligible for variable compensation.</li>
<li>Below is a list of some of the benefits we offer our associates:
</li><li><ul><li>Health: Medical: with competitive plan designs and support for self-care, wellness and mental health. Dental: with in-network and out-of-network benefit. Vision: with in-network and out-of-network benefit.</li>
<li>Wealth: 401(k) with Roth option and matching contribution. Health Savings Account with matching contribution (requires participation in qualifying medical plan). AD&amp;D and supplemental insurance options to help ensure additional protection for you.</li>
<li>Happiness: Paid time off with flexibility to meet your life needs, including 5 weeks of vacation time, 7 health and wellness days, 3 floating holidays, as well as 6 company-paid holidays per year. Paid leave for maternity, paternity and family care instances.</li> 
</ul></li>
</ul></div></div>Pay Range
$98,000 - $169,050 USD</div></div></div>

Senior Data Scientist (P3358) New

Join 84.51° and explore 11   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.