AI/ML Sr. Data Engineer (Sr Systems Analyst)

Our Team

Georgia-Pacific (GP) is among the world's leading manufacturers of bath tissue, paper towels, napkins, tableware, paper-based packaging, office papers, cellulose, specialty fibers, nonwoven fabrics, building products and related chemicals.

Our building products business makes DensGlass® gypsum board often seen in commercial construction, DryPly® plywood and RESI-MIX® wood adhesives, among others.

Our containerboard and packaging business offers high-end graphic packaging to bulk bins as well as Golden Isles fluff pulp.

You may also recognize consumer brands like Angel Soft®, Brawny®, and Dixie® on retail shelves and enMotion® towels, Compact® bath tissue and SmartStock® cutlery dispensers when you are away from home.

Our GP Harmon business is one of the world's largest recyclers of paper, metal and plastics.

As a Koch Company, we create long-term value using resources efficiently to provide innovative products and solutions that meet the needs of customers and society, while operating in a manner that is environmentally and socially responsible, and economically sound.

Headquartered in Atlanta, GA., we employ approximately 35,000 people.

For more information, visit www.gp.com .

To learn more about our culture, Principle-Based Management (PBM®), click here:

https://www.principlebasedmanagement.com

LOCATION: Atlanta, GA

We are seeking a highly motivated, forward thinking Data Engineering professional to support the enterprise GP Collaboration and Support Center's (CSC) Commercial Team and develop custom solutions used across 50+ facilities within multiple divisions.

The CSC functions as a Center of Excellence for all things AI/ML/GenAI for all of Georgia Pacific.

This group creates sustainable value and competitive advantage by leveraging analytics, information, technology, and actionable insights across the enterprise while focusing on futuristic possibilities of analytics.

What You Will Do



* Optimizing AI/ML data science models.


* Standardizing access patterns for data and AWS resources.


* Deploying data pipelines and AI/ML models.


* Aggregating sources and harmonizing data for efficient AI/ML model consumption.


* Orchestrate Sagemaker and SAS models across both SAS and AWS environments.


* Collaborate closely with data science team, operations, and customers dedicated to ensuring proper testing, business outcomes and support.


* Hands on lead for data consolidation and syndication (from various source systems including machine and sensor data in batch, near real-time, and real-time).


* Participate in collaborative software design and development of pipelines and optimizing code on cloud technologies including tools like RedShift, S3, Lambda, Glue and other AWS services.


* Manage own learning and contribute to technical skill building of the team.


* Embrace the engineering mindset and systems thinking.

Collaborate with IT Architect to design forward looking data solution...