Bioinformatics Scientist

Job Title: Bioinformatics Scientist

Function:Delivery

Location:Delhi/Bangalore(3 days in office)

About the Company:

Elucidata is a TechBio Company headquartered in San Francisco. Our mission is to unleash personalized medicine using AI and multi-omics, multimodal data. Elucidata's platform Polly, helps research teams wrangle, store, manage and analyze large volumes of biomedical data. We are at the forefront of driving AI in personalized medicine R&D across companies like Pfizer, Janssen, Owkin and many more. We were recognised as the Most Innovative Biotech Company, 2024, by Fast Company. We are a 120+ multi-disciplinary team of experts based across the US and India. In September 2022, we raised $16 million in Series A round led by Eight Roads, F-Prime, and our existing investors.

About the Role:

We are seeking a Bioinformatics Scientist to curate, harmonize, annotate, and analyze large-scale biological datasets. This role focuses on high-quality data integration and baseline analysis of multi-omic data, especially GWAS/variant data to enable systematic exploration of disease biology. The ideal candidate enjoys working with complex data, applying rigorous QC, and producing reproducible, well-documented outputs.

Key Responsibilities:

• Identify, curate, and harmonize large genomic, transcriptomic and other multi-omics datasets using standardized vocabularies and schemas.
• Perform QC and integrity checks; maintain clear provenance and reproducible processing.
• Conduct baseline comparative analyses of cell types/states and pathway enrichments across datasets.
• Deliver harmonized datasets, annotated objects, and analysis outputs with thorough documentation.
• Collaborate closely with senior scientists and engineering teams to improve workflows and analysis strategies.

Qualifications

• Master's (with 24 yrs experience) or PhD (with 02 yrs experience) in Bioinformatics, Computational Biology, or related field.
• Proven expertise in multiomic data processing
• Experience working with GWAS datasets, including associated downstream analysis tools.
• Proficiency in Python or R for data wrangling and analysis. If proficient in R, there should be sufficient familiarity with python to be able to work with python tools/pipelines.
• Excellent attention to detail, documentation, and reproducibility.
• Strong collaboration and communication skills.

Good-to-have:

• Familiarity with human genetics or immunology.
• Exposure to AWS/cloud-based data transfer and workflows.