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Aspen Technology, Inc. Data Scientist in Bedford, Massachusetts

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

The driving force behind our success has always been the people of AspenTech. Founded more than 30 years ago by the best and brightest engineers at MIT, we continue to tackle the most complex process manufacturing challenges. Our aspenONE software enables our customers to achieve operational excellence by increasing capacity, improving margins, and reducing costs, while becoming more energy efficient, ensuring safety, and shrinking their carbon footprint. This is a place where people are fiercely passionate about technology and have a desire to make a difference through the application of engineering and software technologies to solve real business problems.

As a member of the data science team, you will develop and investigate hypotheses, structure experiments and build mathematical models to understand data patterns and relationships and prescribe actions and options. We are looking for a sharp, disciplined, and highly quantitative individual who has a passion for playing with data, in all its forms including data mining, mathematical modeling and expert systems. We are building a unique technology platform dedicated to the real-time discovery and manipulation of data; this is your chance to be a critical part of that data research team.

Your Impact

  • Develop, maintain, and support new and existing engineering software applications focusing on data science modules.

  • Build and verify mathematical models and automated machine learning tools to analyze and optimize all aspects of our system, providing actionable insights in real time.

  • Productize software using Agile technologies and practices.

  • Demonstrate keen learning of new technologies and methodologies in the area of Data Science.

  • Collaborate with development teams on data selection, preprocessing and formatting for analysis.

  • Learn, understand, and follow software development standards to release products on time; this includes processes such as issue tracking, source code control, coding conventions, Agile ceremonies.

What You'll Need

  • Master Degree or higher in Applied Math, Statistics, Computer Science, or related field.

  • Extensive familiarity with common machine learning and signal processing techniques. Experience with time-series analysis is a plus.

  • Solid understanding of pattern recognition / predictive analysis/ data mining / expert system concepts.

  • Practical experience with data manipulation together with familiarity of available tools to automate data wrangling and data visualization.

  • Ability to prioritize and track multiple projects in parallel and experience running development teams using Agile methodologies.

  • Good interpersonal, presentation and communication skills.

While our impact on the world is big, we offer many of the advantages of a smaller organization. Every employee has a real opportunity to make important contributions that directly benefit our customers and drive our success.

AspenTech is thriving, thanks to our relentless focus on innovation and the dedication of our team of world-class experts who speak more than 10 languages and work in 30 different offices worldwide.

AspenTech is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to age, race, color, religion, creed, sex, sexual orientation, gender identity, national origin, disability, or protected Veteran Status or any other basis protected by federal, state, or local law.

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