Research and Development Intern - Data Analytics - Summer 2025

Role Purpose

The selected candidate will be tasked with utilizing existing data or generating new data to address technical, business, or project-related problems. They should possess experience in data capture using a variety of software tools, management, and manipulation of large data, as well as a comprehensive understanding of numerous data analysis methods. The candidate's analytical tasks will support a wide array of projects, from highly technical issues to business forecasts, encompassing areas like manufacturing, development, research, and commerce. The incumbent will serve as a Subject Matter Expert within a team setting, providing data analytics. This might necessitate the development of innovative computational methods and analytical models. 

Key Responsibilities

• Perform data analysis and provide interpretation of results in RD&E or business environments.
• Work independently or as part of a team on data collection and data preparation, followed by the identification and application of appropriate analytical methods to solve problems or gain insight
• Participate on cross functional teams to develop and test hypotheses to meet project objectives
• Develop new theories or expand upon existing theories as needed to solve complex problems
• Research all external and internal information relative to the problems identified by the project team
• Collaborate with existing subject matter experts to solve very difficult problems in a variety of (mostly technical) disciplines

Experiences/Education - Required

• Pursuing MS or PhD in engineering, computer science, mathematics and statistics, or a related discipline with specialization in data analytics. Preference for candidates with a background in materials science.

Required Skills

• Capable of independently preparing data for machine learning purposes and performing exploratory data analysis.
• Strong mathematical and programming skills
• Deep knowledge of state-of-the-art methods analytical methods and the software required to apply those methods.  Knowledgeable of machine learning techniques, such as traditional machine learning and deep learning algorithms, convolutional neural networks, recurrent neural networks, and reinforcement learning algorithms
• Practical experience of using machine learning and deep learning frameworks and libraries for large-scale data mining

Desired Skills

• Knowledge of emerging technologies and algorithms in computer vision and/or machine learning in general
• Good understanding of analytical platforms and can build data analytics solutions to support the required performance & scale.