Schrödinger, a leader in the field of computational biochemistry, is seeking a Machine Learning Engineer to find insights in dirty chemical datasets.
The ideal candidate will be a data scientist or developer with some experience in writing software and finding insight into medium sized datasets. This is an excellent opportunity for those looking to transition into full-time professional software development while still leveraging a statistics, math, physics, or chemistry background.
Previous experience in professional software development is not required.
A successful candidate will:
- Work well in a collaborative environment
- Run descriptive statistics over sparse and dirty datasets
- Be able to visualize data in interesting unintuitive ways
- Rapidly develop prototype code
- Integrate new/different libraries early and often (e.g. scikit-learn, tensorflow)
- Work with engineers to maintain successful prototypes
Required qualifications include:
- Familiarity with data science and machine learning skills and concepts
- Familiarity with deep learning, neural networks, random forest, support vector machines, and other machine learning techniques
- Excellent written and verbal communication skills
Desirable qualifications include:
- Track record rapidly digesting and reproducing academic learning-based research papers
- Python development experience
- Self Driven
To apply for this job please visit tinyurl.com.