Job Description

We are seeking a Senior Bioinformatics Scientist with a PhD in Bioinformatics or Biotechnology and hands-on experience in clinical projects. The ideal candidate will bring strong expertise across multi-omics data types (single-cell, proteomics, metabolomics) and familiarity with EHR, enabling the delivery of impactful, AI-driven solutions through Elucidata’s platform. In this customer-facing role, you will apply your deep understanding of biology and computational methods to analyze high-dimensional omics data, knowledge graph construction, generate actionable insights, and support our clients in solving complex biological problems. This role is ideal for someone who thrives at the intersection of biology, data science, and customer collaboration, with strong communication skills and a passion for advancing life science research through data.

Key Responsibilities:

• Use your understanding of biological problem statements and multi-omics data to present compelling scientific presentations and develop scalable solutions.
• Analyse multi-omics (genomics, transcriptomics, proteomics, metabolomics, etc) biological data to derive relevant insights using state-of-the-art statistical methods.
• Innovate to 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.

Qualifications:

• 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.

Good-to-have:

• 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.