Work Schedule
Standard (Mon-Fri)
Environmental Conditions
Office
Job Description
Thermo Fisher Scientific is seeking a highly motivated and skilled AI Scientist, Data Sciences to join our Data & AI team in Brno. In this role, you will have the unique opportunity to make a significant impact by developing and integrating impactful AI features. This is done by improving the cleaning, processing, and visualization of application datasets for machine learning (ML) and AI modeling. Also you will perform the training, validation, and later the maintenance of these AI models. You will identify data drift and mitigations with additional datasets or generate synthetic data to optimize our ML applications. Additionally, you will be responsible for hands-on programming and development of custom tools or libraries to optimize the entire data-handling, curation and testing workflow.
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What projects will you work on:
- Build data AI pipelines, architectures, and databases for selected AI applications
- Aggregate disparate datasets for defined AI use cases
- Develop and validate AI applications that meet the requirements of application scientists
- Maintenance of released AI applications
Who do we look for:
- The candidate enjoys working in a multi-cultural, collaborative high-tech data science environment.
- Academic education (MSc degree) in data science, informatics, or software engineering, or equivalent experience.
- Knowledge about data structures, data modeling, and statistics.
- Experience in software design, mainly with Python
- Proactive collaborator and teammate, with an agile mentality
- Willingness to travel, up to 10%
Competencies:
- Proven experience in data management - changing raw data into structured and queryable sets, crafting data pipelines
- Experience in data visualization, e.g., with Matplotlib, Seaborn, Bokeh, Plotly, etc.
- Experience with Pytorch and training testing ML/AI models
You would be part of highly skilled team in AI and digital science that offers plenty of goopportunities to keep up with the rapid developments in the domain.