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 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.