Waters Corporation is looking for a computational scientist to develop, experiment, and validate mechanistic and machine learning models, and support their integration into AWS cloud products for intelligent instrumentation.
Requirements
- 5 or more years of practical experience in mechanistic modeling and machine learning
- Experience in model development using Python for machine learning, statistical, and mechanistic models
- Robust object-oriented and/or functional programming skills in languages including C-Sharp, and Python.
- C++ desirable.
- Comfortable with Git version control, and either BASH or command prompt
- Proficiency with AWS Lambda, S3, EC2, or Redshift desirable
Responsibilities
- Explore various scientific, statistical and machine learning approaches, explore data features, generate metrics, and evaluate results associated with collection and analysis of chromatographic and mass spectrometric data
- Use object-oriented programming and functional programming best practices to maintain codebases in python and C-Sharp, and write unit tests
- Contribute to the construction and maintenance of the AWS data pipeline
- Develop data processing algorithms and models
- Assist with the development of data pipelines for specialty instrument data
- Experiment with new data and algorithmic features to maximize the efficiency and efficacy of the results from our analytical instrumentation
- Maintain up-to-date knowledge of relevant scientific literature
Other
- Assist subject matter experts (SMEs) in model evaluation and stakeholder presentations
- Contribute to the preparation of technical reports, patent applications, and transferable protocols
- Able to communicate results using meaningful metrics and visualizations to managers and stakeholders and receive feedback.
- must be based in Massachusetts
- must have legal right to work in the USA
