Data Scientist

Georgia-Pacific

Atlanta (GA)

On-site

USD 90,000 - 140,000

Full time

2 days ago

Be an early applicant

Get a reply from this employer

Your resume and cover letter, tailored to exactly what they’re hiring for.

Get past ATS filters

Benefits offered by this job

Medical

Dental

Vision

Flexible spending and health savings

Life insurance

Paid vacation/time off

Educational assistance

Parental leave

Retirement

Job summary

Georgia-Pacific in Atlanta, GA is seeking a Data Scientist to join the Collaboration & Support Center Data Science team, focusing on improving manufacturing operations through statistical learning and model-driven insights. You will develop and deploy ML models to enhance safety, efficiency, and performance.

The role covers end-to-end analytics, collaborating with engineering teams, communicating insights to business partners, and delivering MVP solutions in a fast-paced environment.

Qualifications

Bachelor’s degree or higher in a data science-related field such as Engineering Mathematics, Business Analytics, Statistics, Computer Science, or Data Science.
2+ years of experience applying machine learning creatively outside academic datasets, using Python, R, or SAS.
Experience deploying models to production with successful outcomes for users.
Experience with both unsupervised and supervised machine learning.
Experience working with large data sets.
Experience cleaning, manipulating, analyzing, and modeling time series data.
Experience writing and executing complex SQL queries.
Ability to manage and deliver multiple projects in a fast-paced environment.
Ability to work effectively in a collaborative team environment.
Experience using code version control platforms such as GitHub or GitLab.
Legal authorization to work permanently in the United States for any employer without requiring visa sponsorship.

Responsibilities

Own analytics projects from start to finish, including pursuing innovative ideas, developing models, identifying and communicating actionable insights, and implementing solutions to capture value.
Partner with engineering teams to lead end-to-end solution development and scaling for operations-focused (manufacturing) challenges.
Build and maintain relationships with key business partners to support improved decision making.
Maintain focus on delivering minimum viable products that solve most of the issue, while only refining further when critical to safety.
Operate independently and self-manage across project work.

Skills

Strong communication

Collaboration

Project management

Problem solving

Education

Bachelor’s degree or higher in data science-related field

Master’s degree preferred

Tools

Python

SAS

SQL

GitHub

GitLab

Job description

The Data Scientist position supports Georgia-Pacific’s Collaboration & Support Center Data Science team in Atlanta, GA, with a focus on improving manufacturing operations through statistical learning and model-driven insights.

Role Overview

This role develops and deploys statistical, machine learning, and deep learning models aimed at enhancing facility safety, efficiency, and optimal performance. The position supports end-to-end analytics efforts, from early idea exploration through implementation of solutions that capture value.

Responsibilities

Own analytics projects from start to finish, including pursuing innovative ideas, developing models, identifying and communicating actionable insights, and implementing solutions to capture value.
Partner with engineering teams to lead end-to-end solution development and scaling for operations-focused (manufacturing) challenges.
Build and maintain relationships with key business partners to support improved decision making.
Maintain focus on delivering minimum viable products that solve most of the issue, while only refining further when critical to safety.
Operate independently and self-manage across project work.

Required Qualifications

Bachelor’s degree or higher in a data science-related field such as Engineering Mathematics, Business Analytics, Statistics, Computer Science, or Data Science.
2+ years of experience applying machine learning creatively outside academic datasets, using a formal programming language such as Python, R, or SAS.
Experience deploying models to production with successful outcomes for users.
Experience with both unsupervised and supervised machine learning.
Experience working with large data sets.
Experience cleaning, manipulating, analyzing, and modeling time series data.
Experience writing and executing complex SQL queries.
Ability to manage and deliver multiple projects in a fast-paced environment.
Ability to work effectively in a collaborative team environment.
Experience using code version control platforms such as GitHub or GitLab.
Strong communication and collaboration skills, including gathering, translating, and implementing business requirements and feedback into technical solutions.
Legal authorization to work permanently in the United States for any employer without requiring visa sponsorship.

Technologies

Python
R
SAS
SQL
GitHub
GitLab

Preferred Experience

Master’s degree or higher in a data science-related field such as Data Science, Mathematics, Engineering, Statistics, Computer Science, or Business Analytics.
Experience using SAS for statistics or machine learning.
Experience with data manipulation, computing, memory, optimization, and cloud computing (AWS).
Experience with SAS Event Stream Processing (ESP).
Experience working with Manufacturing Operations.
Experience working with IoT data.
Proven experience designing, building, and productionizing GenAI solutions, including prompt engineering, RAG, LLMs, agentic AI, and model evaluation.
Knowledge of MLOps best practices, including CI/CD pipelines and model lifecycle management.
Experience using AI-powered development tools and coding agents (e.g., Devin, Cursor) to improve productivity.

Benefits