Analytics & Data Consumption Co-op

Novelis Global R&T•Kennesaw, GA

2d•Onsite

About The Position

The OT Data Management team, located in Kennesaw, Georgia, is seeking an Analytics & Data Consumption Coop. This role will help transform validated OT data into actionable insights through analytical models, standardized KPIs, operational benchmarking, dashboards, and scalable data products. The coop’s primary project will focus on developing and evaluating AI-enabled insights on top of trusted OT datasets in Databricks, with attention to business relevance, data quality, traceability, and clear communication of results.

Requirements

Currently enrolled in an accredited bachelor’s or master’s degree program in Data Science, Computer Science, Engineering, Analytics, Information Systems, Statistics, or a related field.
Foundational experience with Python and SQL for data preparation, analysis, or model development.
Ability to analyze data, investigate inconsistencies, and communicate findings clearly.
Interest in manufacturing, operational technology data, industrial analytics, or digital transformation.
Ability to work collaboratively, manage assigned tasks, and document work in a structured and reproducible manner.

Nice To Haves

Experience with Databricks, Spark, Delta Lake, or cloud-based data platforms.
Experience developing Power BI reports, semantic models, or data visualizations.
Exposure to machine learning, generative AI, natural-language interfaces, or AI-assisted analytics.
Familiarity with data pipelines, data quality testing, KPI validation, or analytical model testing.
Experience with Git or other version-control and collaborative development practices.
Knowledge of manufacturing processes, time-series data, or operational performance metrics.
Strong written communication skills and an interest in translating technical analysis into business insights.

Responsibilities

Support the development, testing, and validation of AI-enabled insights using validated OT data in Databricks.
Prepare and curate analysis-ready datasets for operational and manufacturing use cases.
Develop and validate analytical models, business rules, and standardized KPI calculations.
Evaluate AI-generated findings against source data, established KPIs, and operational context to improve reliability and usefulness.
Create or enhance Power BI reports, dashboards, and other data-consumption solutions for business stakeholders.
Perform data quality assessments and document issues, assumptions, validation results, and recommended actions.
Support cross-plant benchmarking and operational performance analytics.
Contribute Python and Databricks development under the guidance of OT Data Management team members.
Document analytical methodologies, dataset lineage, model logic, and user guidance to promote reuse and adoption.
Support value-tracking activities by connecting analytical outputs to measurable operational opportunities.