Bioinformatics Scientist

Multi-Omic Integration & Functional Follow-up

DataTecnica | Remote/Flexible | Full-time (2,000 hours per year contracting)

About DataTecnica

DataTecnica is a biomedical AI company specializing in analytics for neurological and other diseases. We work at the intersection of large-scale genomics, clinical data, and translational research—partnering with major initiatives from academia and non-profits to tech including large scale collaborative efforts like the Global Parkinson's Genetics Program (GP2), and the NIH’s Center for Alzheimer’s and Related Dementias (CARD). Our team has contributed to over 700 peer-reviewed publications in neurogenetics and neurodegenerative disease research.

About the Role

We're hiring a Bioinformatics Scientist to lead post-GWAS follow-up and multi-omic integration for precision medicine initiatives in Parkinson's disease. You'll take genetic signals from our GWAS pipeline and build the biological context needed to better understand function, informing future CRISPR studies and then participating in those efforts. This role sits at the intersection of network biology, functional genomics, and translational research and genetics.

What You'll Do

Primary Responsibilities (70%)

• Vet and maintain best-practices bioinformatic pipelines
• Process multi-omic data from transcriptomics to CRISPR screens
• Conduct network community detection analyses (Louvain, WGCNA, MEGENA) using PPI and co-expression networks
• Perform pathway enrichment and functional annotation of candidate gene sets (GO, KEGG, Reactome,GIdb, ChEMBL, and Open Targets)

Secondary Responsibilities (30%)

• Basic GWAS QC and association testing to maintain familiarity with upstream genetic data and in some instances execute GWAS
• Interpret and contextualize GWAS results (Manhattan plots, regional association plots, LocusZoom)
• Support colocalization and SMR analyses as needed
• Collaborate on genetic and biomarker integration studies in an open science context

Required Qualifications

Preferred Qualifications

• Experience with neurodegeneration and brain-related omics datasets
• Familiarity with proteomics data analysis (mass spec, SomaScan, Olink)
• Experience with pathway databases and interaction resources
• Knowledge of CRISPR screening data analysis
• Knowledge of spatial transcriptomics and/or proteomics
• Experience with graph databases and/ or knowledge graphs for biological data

Technical Environment

You'll work across cloud platforms including Terra, Verily Workbench, and UK Biobank RAP. Our pipelines leverage containerized workflows (Docker, Singularity) and workflow managers (WDL, Snakemake, Nextflow) and potentially HPC. High-memory compute for network analyses is available.

To Apply

Submit CV and cover letter with links to 2-3 representative publications demonstrating post-GWAS / bioinformatics methodology expertise as well as related GitHub content.

Compensation

$100,000 to $200,000 / year total compensation commensurate with experience. Multiple positions at various levels of seniority exist for this role.