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Data Scientist
INFICON in East Syracuse, New York
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Date Posted 07/07/2020
Science-Computer Sciences
Employment Type Fulltime
Application Deadline Open until filled


INFICON is a growing, global, leading provider of innovative technologies that enhances productivity and quality in sophisticated industrial processes. The products provided by INFICON are world-class instruments for gas analysis, measurement, and control and are vital to manufacturers and end-users in the complex fabrication of semiconductors and thin film coatings for optics, flat panel displays, solar cells, and industrial vacuum coating applications. INFICON is headquartered in Switzerland and has world-class manufacturing facilities in Europe, the United States and China with subsidiaries located throughout the world.  This position will be located in East Syracuse, NY.  For more detailed information about INFICON, please visit our website at www.inficon.com.  


INFICON's Data Science Research group in East Syracuse NY conducts research to analyze data from sensors and  automatically identify events of critical importance to our customers.  Our group develops algorithms to process faint signals buried in noisy spectral data so that we can build advanced semiconductors or protect people's lives from deadly chemicals. 

You will apply your mastery of state-of-the-art machine learning technologies to difficult problems on noisy high-dimensional data. You will work in a multi-disciplinary team that includes experts in Computer Science, Mathematics, Chemistry, Physics, Electronics, and Advanced Semiconductor Manufacturing Processes.  Your research will have high visibility because of its potential to greatly increase the value of our products.   

In this job, you will be given ample freedom and flexibility to explore a wide range of novel approaches, you will work closely with your colleagues, on large amounts of sensor data and you will always remain focused on writing high value code.


  • Research and develop algorithms for identification of compounds in sensor data from instruments  

  • Research and develop anomaly detection algorithms or multivariate time-series data

Required background:

  • PhD or equivalent in Computer Science or Applied Mathematics, with specialization in Data Science and Machine Learning.  Candidates without a PhD are encouraged to apply- that have the experience to solve challenging data science problems

  • Fluency with Python, Linux, Scientific Computing Libraries, Machine Learning Libraries

  • Accomplished Software Developer with experience training and testing ML modules on large high-dimensional data sets  

 Preferred background:

  • Demonstrated ability with statistical ML and with neural networks

  • Published papers and/or code for analyzing sensor data or process control data

  • Prior work with unsupervised or semi-supervised ML for anomaly detection

  • Experience with pyTorch or Tensorflow

  • Experience with multivariate time series analysis and modeling techniques

  • Knowledge of Physics or Chemometrics or Process Control

  • C++ Software Development

Compensation will be commensurate with experience including a competitive salary, discretionary bonus opportunity, competitive benefits package, and relocation assistance.

INFICON, is committed to ensuring that our online application process provides an equal opportunity to all job seekers that apply without regard to race, religion, ethnicity, national origin, citizenship, gender, age, protected veteran status, disability status, genetic information, sexual orientation, or any other protected  characteristic.  A notice describing Federal equal employment opportunity laws is available here and here to reaffirm this commitment.  

INFICON is also committed to providing reasonable accommodations to applicants with physical and/or mental disabilities.  If you are interested in applying for an employment opportunity at INFICON and require special assistance or an accommodation during the application process, please contact Human Resources at 315-434-1100.  Determination on requests for reasonable accommodations are made on a case-by-case basis.


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