Jobs at Ahold Delhaize USA

Coordinates the intake, prioritization, execution, validation, and delivery of promotional offers across digital and traditional marketing channels. Maintains calendars, schedules, trackers, and workflow tools; monitors deadlines, risks, quality assurance, and launch readiness. Collaborates with marketing, merchandising, loyalty, creative, digital, pricing, ecommerce, operations, and external partners. Prepares operational reports, supports troubleshooting, documents procedures, and identifies process improvements.

Supports strategic initiatives for a grocery retail organization by co-developing recommendations, conducting analyses, preparing presentations, participating in strategy discussions, and assisting with reporting and ad hoc projects. The internship includes mentorship, leadership development, networking, and opportunities to present work to company leaders in a hybrid office environment.

Leads advanced analytics, machine learning, and AI initiatives for Finance, developing predictive models, forecasting solutions, optimization, automation, anomaly detection, and conversational analytics. Partners with Finance, Data, Technology, and Engineering teams to translate business challenges into scalable solutions, establish governance and testing frameworks, evaluate model performance and bias, and drive adoption. Provides technical leadership and mentorship while supporting Finance transformation and continuous improvement.

Performs lease accounting and month-end close activities, including journal entries, reconciliations, financial reporting, forecasting, variance analysis, and audit support. Reviews ledger activity, ensures GAAP and compliance adherence, resolves financial issues, and recommends corrective actions. Leads process improvement using Lean Six Sigma, supports special projects, standardizes reporting processes, and mentors other associates while partnering across Finance, Real Estate, and business teams.

Supports the FP&A team with financial analysis, reporting, planning deliverables, data synthesis, standardized templates, and process improvement. The intern collaborates with FP&A colleagues, analyzes financial results, identifies efficiency opportunities, and recommends actionable solutions while developing finance, analytical, and business skills through mentorship and project work.

Supports pricing and promotion planning and execution across retail brands by managing systems, processes, requirements, issue resolution, testing, implementation, training, and adoption. Serves as a subject matter expert for DemandTec, Revionics, legacy platforms, data integrations, and commercial modernization initiatives. Partners with business, IT, data, vendors, and change-management teams to standardize workflows, define future-state capabilities, improve automation, and support enterprise pricing and promotion solutions.

Maintains and evolves common product hierarchies and category roles across assigned grocery portfolios. Establishes taxonomy guidelines, resolves categorization discrepancies, facilitates governance forums, and partners with merchandising, pricing, data, and insights teams. Uses market trends, consumer insights, competitive data, and syndicated/internal data to improve product placement, accuracy, consistency, and customer relevance. The role also supports change management, documentation, stakeholder advocacy, and continuous process improvement.

The Platform Engineer II designs and operates enterprise observability capabilities, including synthetic monitoring, SNMP telemetry, dashboards, alerts, event correlation, and integrations with ServiceNow. The role supports metrics, logs, and traces across applications and infrastructure; automates platform tasks; onboards services; troubleshoots monitoring systems; supports upgrades and incidents; and partners with engineering, infrastructure, SRE, and operations teams to improve reliability and reduce alert noise.

Designs and maintains reusable data ingestion and transformation components, automated quality and governance checks, reliable pipelines, monitoring, deployment automation, cloud integrations, containers, and infrastructure as code. Partners with data consumers on usable models and datasets, documents standards and runbooks, supports Agile improvement, and responds to critical IT incidents. Requires 5+ years of data engineering experience, orchestration, distributed processing, storage, scripting, automation, and version control expertise.

Manage a caseload of workers' compensation claims across jurisdictions: investigate compensability, control medical care, negotiate settlements, coordinate return-to-work, partner with internal teams and vendors, identify fraud, and ensure compliant, cost-effective claim resolution while supporting injured associates.

Owns the vision, roadmap, governance, and lifecycle management of AI/ML platform capabilities. Translates stakeholder needs into platform requirements, prioritizes integrations and improvements, partners with engineering teams, drives adoption, and monitors reliability, performance, security, cost, and technical debt. The role also supports agile delivery, communicates releases and incidents, reports progress to leadership, and assists with critical IT escalations.

Designs scalable data and AI platform architectures, reusable ingestion and transformation patterns, automated governance and CI/CD workflows, secure cloud infrastructure, observability, and infrastructure-as-code environments. The role improves platform reliability, scalability, and developer productivity through tooling, golden paths, monitoring, automated recovery, and technical standards. It also provides architectural guidance, coaches data teams, and supports critical IT incidents.

Develops and oversees enterprise AI governance policies, standards, controls, monitoring, and risk-management processes. Advises business and technology leaders on responsible AI, regulatory requirements, controls, and mitigation strategies. Coordinates with cybersecurity, privacy, legal, compliance, architecture, and engineering teams; evaluates control effectiveness; drives corrective actions; supports audits, executive reporting, and governance committees; and promotes adoption through stakeholder education. Requires 8+ years in data analysis, reporting, or related fields, with SQL, analytics, data modeling, and visualization experience.

Designs reusable data ingestion and transformation components, automates data quality, governance, testing, lineage, and deployment workflows, and improves pipeline observability and reliability. The role supports monitoring, incident response, cloud and container integrations, infrastructure as code, documentation, reusable datasets, and Agile platform improvements. Candidates need five or more years of data engineering experience plus expertise in orchestration, distributed processing, storage, scripting, automation, and version control.

Implements data pipelines and platform features, automates validations and operational tasks, supports CI/CD and infrastructure-as-code changes, monitors platform reliability, assists with migrations and performance tuning, and maintains technical documentation. The role also contributes to data quality, incident response, cloud configuration, and incremental platform improvements. This is a hybrid position with potential urgent IT incident support responsibilities.

Performs data analysis, cleans and validates data, identifies trends and anomalies, builds dashboards and reports, and supports KPI development. Collaborates with engineers and business stakeholders to improve data quality, pipelines, reporting requirements, and analytical processes. Leads data-driven change management, communicates insights, shares best practices, and may support urgent IT incidents.

Develops, tests, evaluates, and deploys machine learning models using established architectures and frameworks. Supports feature engineering, data preprocessing, automated training and monitoring pipelines, and production AI integration. Collaborates with engineering and product teams on AI requirements, researches methods to improve model performance, and supports urgent IT incidents. The role requires strong Python and machine learning experience, knowledge of deep learning and generative AI, and advanced quantitative education.

Leads enterprise data science and AI solution delivery, including ML, generative AI, and predictive model development, deployment, monitoring, governance, and integration into business workflows. Drives AI adoption, change management, value realization, and evaluation of emerging technologies while partnering with data, engineering, and platform teams. Builds and leads AI delivery teams and ensures compliance with security and governance standards.

Develop, test, deploy, and serve machine learning models and agentic AI capabilities. Build feature engineering, experimentation, training, monitoring, and REST-based model-serving workflows. Collaborate with data science, engineering, product, and MLOps teams to productionize AI solutions at enterprise scale using distributed computing, Databricks, cloud platforms, and containerized infrastructure. Support model performance improvements, generative AI initiatives, and urgent IT escalations.

Leads technical delivery, support, configuration, testing, and continuous improvement for warehouse management systems, with Manhattan Active preferred. Serves as a technical subject matter expert, translates business needs into requirements, partners with engineering and product teams, manages suppliers, leads complex projects, performs root cause analysis, and ensures stable 24/7 operations. Coaches analysts and supports implementations, production turnover, system monitoring, and post-production stabilization.