Bayer is looking to analyze and interpret complex protein sciences data to derive actionable insights and support decision-making processes, and to develop and implement data strategies that facilitate the integration of machine learning and deep learning methodologies.
Requirements
- Strong understanding of protein structure, function, and bioinformatics tools;
- Proficiency in programming languages such as Python or R, with experience in data manipulation and analysis libraries (e.g., Pandas, NumPy) with familiarity in AWS SageMaker;
- Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and statistical analysis techniques.
Responsibilities
- Analyze and interpret complex protein sciences data to derive actionable insights and support decision-making processes;
- Develop and implement data strategies that facilitate the integration of machine learning and deep learning methodologies;
- Create data visualizations and reports to communicate findings to both technical and non-technical stakeholders;
- Assist in the development of predictive models and algorithms to enhance protein structure-function predictions;
- Contribute to the development of code, models, and end-to-end workflows for the analysis of text, protein sequences, and protein characterization data;
- Stay up-to-date with the latest advancements in data science, machine learning, and protein sciences to inform project strategies;
Other
- Collaborate with the Protein Sciences (PS) and data science and intelligence(DSI) team to understand project goals and identify key decision points in the research pipeline;
- Comply with all safety, stewardship, and IT/information security policies and regulations.
- Currently pursuing a degree in Data Science, Bioinformatics, Computational Biology, or a related field, with a focus on protein sciences;
- Excellent problem-solving skills and the ability to work collaboratively in a team environment;
- Strong communication skills to effectively present complex data findings.
