Data Science Internship — Hybrid, End-to-End Analytics

Flint Hills Resources; Atlanta (GA); Híbrido; USD 28.000 - 36.000; Jornada completa

Descripción de la vacante

Georgia-Pacific’s Data Science Internship in Atlanta, GA invites students to join for a 12-week hybrid program from mid-May to early-August 2027. You will work with a team of data scientists to build scalable statistical and machine learning solutions for manufacturing operations, partnering with engineers and business teams.

As an intern, you’ll own analytics projects end-to-end, develop and deploy models, and communicate insights to drive safer, more efficient operations.

Formación

• Bachelor’s degree or higher in a data science-related field (Engineering, Math, Analytics, CS).
• Experience applying statistical analysis and machine learning using Python and/or SAS.
• Experience using SQL to retrieve data.
• Eligible for full-time employment in the United States by Summer 2028.
• Legal authorization to work permanently in the United States without visa sponsorship after graduation.

Responsabilidades

• Analytics project ownership from start to finish – pursuing innovative ideas, developing models, communicating actionable insights, and implementing solutions to capture value.
• Work with various engineering teams, own end-to-end solution development and scaling focused on Operations (manufacturing) challenges.
• Partnership: develop and maintain relationships with key business partners to enable improved decision making.

Conocimientos

Statistical analysis

Machine learning

Python

SQL

Educación

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

Herramientas

SAS

Descripción del empleo

Georgia-Pacific’s Data Science Internship in Atlanta, GA invites students to join for a 12-week hybrid program from mid-May to early-August 2027. You will work with a team of data scientists to build scalable statistical and machine learning solutions for manufacturing operations, partnering with engineers and business teams.

As an intern, you’ll own analytics projects end-to-end, develop and deploy models, and communicate insights to drive safer, more efficient operations.