Bioinformatics Scientist
7 days ago
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 2–4 yrs experience) or PhD (with 0–2 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.
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