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 RoleAs a Senior Principal Data Scientist in our rapidly growing Technology Group, you will provide technical leadership for teams that are developing innovative solutions for the next generation of Asset Performance Monitoring AI. We are looking for sharp, disciplined, and highly quantitative individuals who have a passion for playing with data, 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 drive AspenTech’s Asset Performance Monitoring strategy by developing ground-breaking software.Your Impact
- Provide technical leadership to teams of data scientists, engineers, and software developers to develop new machine learning and cognitive computing applications for the manufacturing and process industries.
- Collaborate with customers, product managers and technical staff to develop technology strategies to promote continuous innovation in our Asset Performance Monitoring solution offerings.
- 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 represent AspenTech at industry and academic meetings and conferences.
What You'll Need
- Master’s in Computer Science, Engineering, or a related major; PhD preferred.
- 12+ years of experience in data analysis and software development/programming.
- Experience with C++, C#, Python.
- Experience with machine learning algorithms. (regression, semi-supervised learning, transfer learning, deep learning, reinforcement learning, time series analysis, predictive modeling, data mining, cognitive computing, natural language processing)
- Experience with big data and cloud technologies.
- History of publishing research and results in the ML field.
- Participated in the design, development, evaluation, and deployment of scalable data-driven models and analytical solutions for machine learning application.
- Problem-solving ability and attention to details.
- Demonstrated ability to use scientific research to deliver value to customers and are motivated to deliver results in a fast-paced environment.
- Excellent interpersonal, communication, writing, and presentation skills.
- Demonstrated ability to convey complex information in a clear and concise manner.