Data Scientist, Research
vor 7 Monaten
**Primary Work Location**:
Berlin
**Overview**:
**Professional Qualifications**:
**Education**:
Bachelor's degree in applied Statistics, Data Science, or Applied Mathematics preferred. Bachelor's degree in science, Technology, Engineering or Math (STEM) field with an emphasis on algorithmic development, signal processing, and data analysis will be considered.
**Experience**:
- Minimum of three (3) years of post-graduate academic or commercial experience in analyzing large data sets.
- Familiarity with Machine Learning (ML) and Artificial Intelligence (AI) theory and related software tools a plus.
- Demonstrated ability to synthesize new algorithms for data analysis and presentation.
- Experience with implementing data processing for embedded systems and familiarity with edge computing a plus.
- Experience with code repository tools such as Git (Gitlab, Github) a plus
**General**:
- Demonstrated ability to draw conclusions and effect decisions through data analysis and interpretation.
- Creativity, and the ability to synthesize and clearly communicate results to a diverse audience is a requirement. Analysis skills alone are not enough.
- Excellent communication (verbal/written), interpersonal, organization, and presentation skills; must be able to clearly present to a variety of audiences.
- Motivated self-starter who can operate independently with little direct oversight.
- Dependable, teachable, team player, positive attitude, and good attendance.
**Position Responsibilities**:
**Specific**:
- Perform post-processing data analysis using datasets from LI-COR systems to evaluate performance and diagnose issues.
- Proactively explore, develop and test models to improve instrument and system performance based on experimental results.
- Manage statistical analysis code using source repository tools such as Gitlab.
- Write and test production quality code for on-board data processing (edge-computing) within instruments, in either OS (Linux) or microcontroller environments.
- Write and test production quality code for post-processing data analysis and synthesis tools, either desktop or cloud based.
- Proactively explore and propose added-value data products that can be extracted, also using ML and AI technologies, from field measurements collected by networks of instruments.
- Interact with scientists and other end users to explore solutions and co-developments.
**General**:
- Maintain awareness of current methods and trends in data science.
- Review trade publications and attend relevant trade shows.
- Moderate travel is required to customer sites, conferences, and trade shows.
- Other duties as assigned.
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