AI & Gen AI - Products & Tools E2
acestackChicago (IL)
About the role
Job Title:
AI & Gen AI - Products & Tools E2Location: Chicago, IL (ONSITE)FULLTIME ONLYJob Description Must Have Technical/Functional SkillsThe AI / ML Architect will lead the design and evolution of enterprise scale AI and Machine Learning platforms supporting Retail Measurement, Consumer Panel Data, Omnichannel Analytics, and Advanced Insights. This role ensures AI solutions are scalable, explainable, governed, and production ready, enabling faster insights for retailers, manufacturers, and internal analytics teams. The role bridges business stakeholders, data science, platform engineering, and cloud architecture, driving AI adoption across consumer behavior modeling, demand forecasting, pricing, promotions, and shopper analyticsAI / ML & Analytics Strong experience in Machine Learning, statistical modeling, and applied analytics. Hands on expertise with Python and ML frameworks Experience applying AI to retail, consumer analytics, or large observational datasets.
Roles & Responsibilities
Key Responsibilities: Define end to end AI/ML architecture for retail and CPG analytics use cases:
- Consumer panel modeling
- Omnichannel shopper behavior
- Demand forecasting & assortment optimization
- Price & promotion effectiveness
- Product hierarchy & attribution models
- Design reusable AI reference architectures aligned to NIQ's data platforms (lakehouse, curated marts, analytical services).Data Driven AI Platforms
Architect AI solutions leveraging large scale transactional, panel and digital commerce data.
Partner with Data Architecture teams to ensure:
Feature engineering standards
High quality, reusable analytical datasets
Alignment with product agnostic / common sample analytics strategies
Enable AI models to integrate seamlessly with reporting, dashboards, APIs, and client facing products.
MLOps & Platform Enablement
Define and standardize MLOps pipelines for:
Model training, validation, deployment, and monitoring
Versioning, reproducibility, and lineage
Performance and data drift detection
Support multi-tenant AI platforms used by multiple analytics teams and geographies.
Collaborate with DevSecOps to embed security, resiliency, and cost optimization.
Responsible AI & Governance
Establish AI governance frameworks suitable for:
Client facing analytics products
Explainability and transparency requirements
Regulatory and data privacy constraints (GDPR, data usage agreements)
Ensure models are auditable, explainable, and compliant with data policies.
Define controls for ethical AI, bias detection, and model approval workflows.
Data & Platform Architecture:
Experience designing distributed data and AI platforms (Snowflake, Databricks, lakehouse architectures).Strong understanding of feature stores, model registries, and experiment tracking. Familiarity with API driven analytics delivery.
Cloud & Engineering:
Strong experience with cloud platforms (Azure preferred; AWS/GCP acceptable).Knowledge of containerization and orchestration (Docker, Kubernetes).Experience integrating AI with enterprise data products and analytics services.
Governance & Enterprise Readiness:
Knowledge of data governance, privacy, lineage, and auditability.
Experience implementing Responsible AI practices in enterprise environments.
Strong documentation and design communication skills.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
More like this
