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2 days ago
A senior bioinformatics scientist plays a crucial role in delivering impactful AI-driven solutions through our platform.
This customer-facing position requires a deep understanding of biology and computational methods to analyze high-dimensional omics data, construct knowledge graphs, generate actionable insights, and support clients in solving complex biological problems.
- Present compelling scientific presentations and develop scalable solutions based on expertise in biological problem statements and multi-omics data.
- Derive relevant insights from multi-omics (genomics, transcriptomics, proteomics, metabolomics, etc) biological data using state-of-the-art statistical methods.
- Develop and optimize tools, pipelines, and algorithms for the analysis and visualization of multi-omics biological data.
- Contribute to the ideation & deployment of knowledge graphs and structured data models, ensuring datasets are AI/ML-ready for downstream applications.
- Collaborate with a diverse team of ML specialists, data scientists, and bioinformatics engineers to translate customer requirements into innovative solutions.
- Work closely with technical owners and solution managers to foster account growth and nurture customer relationships.
- PhD (with 0-2 years of relevant experience) or Masters (with 3-5 years of relevant experience) in Bioinformatics, Computational Biology, Biotechnology or related technical discipline with demonstrated work in clinical projects.
- Proven expertise in processing and analyzing omics data using predefined/custom end-to-end analysis workflows to derive actionable insights and clinical data integration.
- Proficient in a programming language used for data analysis such as Python or R.
- Hands-on experience applying computational algorithms and statistical methods to structured and unstructured big data.
- Track record of successful collaboration and independent work.
- Excellent communication and presentation skills, with the ability to work effectively in a collaborative environment.
- Exposure to EHR data integration for clinical and translational research.
- Experience with spatial omics data analysis and interpretation.
- Familiarity with AI/ML applications in biomedical data analysis.
- Experience working with cloud technologies and scalable computing platforms.
- Previous experience in customer collaboration and successful project delivery.
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