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Genomic Data Analyst

Genomic Data Analyst

ElucidataBengaluru, Republic Of India, IN
26 days ago
Job description

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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