Rotational Development Program, AI & Data

About the Role

PennEngineering is seeking a motivated individual to join the PennEngineering AI and Data Rotational Program. This program offers a unique opportunity to gain hands-on experience with data and apply AI techniques to real-world problems. Rotational assignments will involve working with the Information Services team, AI and Data Teams, and within business units. The objective is to learn how to support the design, development, and implementation of AI-driven solutions that optimize business operations.

Rotational Structure

• First rotation: Data Engineering and Data Visualization teams.
• Second and third rotations: Within one of our business units at locations within the US or globally.

Key Responsibilities

• Data Handling/Exploration: Collect, preprocess, analyze, and visualize large datasets to identify trends and patterns.
• Model Development: Assist in developing machine learning models for regression, classification, time series, natural language processing (NLP), and clustering applications. This includes performing customer behavior analysis, prospect valuation, and process optimization.
• Support AI Tool Development: Assist in the design, development, and implementation of AI-based solutions to enhance company processes.
• Collaboration: Work closely with cross-functional teams to understand business problems and requirements, and integrate Data & AI solutions into existing workflows.
• Research: Stay updated with the latest advancements in AI and machine learning and suggest innovative techniques to improve tool performance.
• Documentation: Maintain comprehensive documentation of AI/ML models, processes, and results.
• Risk Assessment: Contribute to organizational strategies for identifying and managing the risks of deploying Data & AI applications, focusing on user experience and human factors.

Requirements & Tech Stack

• Education: May 2027 graduate with a bachelor’s or preferably a master’s degree in Computer Science, Computer Engineering, Artificial Intelligence, or Data Science.
• Programming Languages: Proficiency in Python, R, and/or SQL.
• Machine Learning: Basic knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, tidymodels, keras).
• Data Concepts: Understanding of data preprocessing, feature engineering, and model evaluation techniques.
• Databases: Familiarity with relational and NoSQL databases.
• Version Control: Proficiency with version control systems like Git.
• AI Agents: Experience building AI agents to perform tasks, analyze data sets, and summarize findings.
• Cloud Platforms: Familiarity with AWS or Azure for deploying data solutions is a plus.
• Data Visualization: Exposure to data visualization tools such as Qlik, Tableau, Power BI, or similar.
• Learning Aptitude: Eagerness to learn and stay updated on emerging data science and AI technologies.

Additional Skills

• Problem-solving and analytical skills.
• Strong communication (verbal and written) and collaboration abilities.
• Detail-oriented with a focus on delivering high-quality solutions.
• Strategic thinking to align AI initiatives with business goals.
• Innovative mindset with enthusiasm for exploring new AI technologies.