Analytics/AI Intern

Job Description

Analytics/AI Intern | Peabody

The Tone:
This is a full-time internship at Peabody, located in St. Louis, MO. Peabody is a leading global coal producer, supplying essential products crucial for affordable, reliable energy and steel production. In this role, you will contribute directly to cross-functional initiatives by applying data analytics, machine learning, and AI tools to drive business insights and optimization. This is an exciting opportunity to develop your skills within an organization committed to sustainability and an inclusive work environment.

The TL;DR
• Role: Internship
• Type: Full-time
• Location: St Louis, MO (Hybrid)
• Pay: $20–$27 hourly
• Team: Reports directly to the Sr. Manager, Analytics & Automation.
• Mission: To utilize data analytics, machine learning, and AI technologies to generate actionable business insights and enhance operational efficiency across various company initiatives.
• Tech Stack: Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch), Power BI, Tableau, Excel, SQL

What You’ll Actually Do
• Analyze Data: Support data preparation and analysis for ongoing projects.
• Create Dashboards: Assist in building dashboards and reports using Power BI or similar tools.
• Develop Models: Contribute to machine learning model development and explore AI techniques for automation and innovation.
• Build Prototypes: Construct models or prototypes using AI/ML technologies to deliver insights.
• Communicate Findings: Document workflows, findings, and recommendations for internal stakeholders.

The Must-Haves
• Background: Currently pursuing a degree in Computer Science, Data Science, Engineering, Statistics, or a closely related quantitative field, demonstrating a foundational understanding of data-driven principles.
• Experience: Demonstrated skill in Python, including practical experience with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch. Exposure to data visualization tools like Power BI, Tableau, or Excel is essential, alongside a strong understanding of SQL and relational database concepts.
• Skills: A solid theoretical and practical foundation in machine learning algorithms and core statistical concepts. Excellent analytical abilities, strong problem-solving acumen, and clear, effective communication skills are critical for collaborating with internal stakeholders.