Data Science Intern

The driving force behind our success has always been the people of AspenTech. What drives us, is our aspiration, our desire and ambition to keep pushing the envelope, overcoming any hurdle, challenging the status quo to continually find a better way. You will experience these qualities of passion, pride and aspiration in many ways — from a rich set of career development programs to support of community service projects to social events that foster fun and relationship building across our global community.

The Role

As a Data Science Intern in our Technology Group, you bring deep technical expertise in developing innovative solutions for the next generation of AspenTech’s Engineering Product Suite. We are looking for sharp, disciplined, and highly quantitative individuals who have a passion for playing with complex data and cutting-edge technologies, in all its forms, including data mining, mathematical modeling, cognitive computing and expert systems. You will leverage your skills and passion for Machine Learning, AI and Cognitive Computing to innovate AspenTech’s Engineering Design and Simulation suite and help develop ground-breaking software.

Your Impact

• Collaborate with data scientists, engineers, and software developers to innovate new functionality like and Aspen Virtual Advisor extension for the engineering portfolio.
• Investigate new and developing technologies as they appear in industry and academia and determine how to leverage these new technologies into our software applications.
• Provide thought leadership and present your research in our AI Projects meeting.

What You'll Need

• Enrollment in an Engineering, Operation Research, or a related major University program.
• Early knowledge of data analysis and software development/programming with one or more of Python, Julia, Matlab, C++/C and C#.
• Knowledge in engineering mathematics, statistics and optimization.
• Drive to learn algorithms (regression, semi-supervised learning, deep learning, reinforcement learning, time series analysis, predictive modeling, data mining, cognitive computing).
• Exposure to LLM, generative AI, MLops, Graph Knowledge, and/or cloud technologies is a plus.
• Problem-solving ability and attention to details.
• Excellent interpersonal, communication, writing, and presentation skills.
• Demonstrated ability to convey complex information in a clear and concise manner.