(Associate) Scientist, Health Data

Variant Bio is developing life-saving therapies by studying the genes of people with exceptional health-related traits. By identifying communities with unique genetic architectures and outlier phenotypes, Variant Bio has identified novel human genetic evidence that is the basis for programs with breakthrough potential across multiple therapeutic areas. The company's research is powered by its proprietary Inference platform , which integrates across deep phenotyping and multi-omic data using statistical genetics and AI/ML approaches to identify and validate therapeutic targets.

In addition, Variant Bio has established strategic partnerships with Novo Nordisk and Boehringer Ingelheim , validating the strength of the platform and enabling the advancement of novel therapeutic programs through world-class development expertise.

Benefits

that directly impact the communities it partners with throughout the world.

ABOUT THE ROLE

The Health Data team at Variant Bio turns data generated in the field, across our international partner cohorts, into harmonized, analysis-ready resources that power genetic target discovery. We are looking for someone who enjoys the challenge of complex, real-world data and is motivated to build robust, reproducible solutions for maximizing its quality and comparability across studies, modalities, collaborators, and collection sites. In this role you will own the curation, quality control, and harmonization of multi-omic, survey, biochemistry, and clinical data as it arrives from field sites around the world.

You will help develop the standards and pipelines that keep that data trustworthy at scale, spanning the full path from bench work to downstream analysis. Success in this role depends on good scientific judgment about how data is produced: an instinct for where recruitment, sampling, batching, or measurement can introduce bias in genomic studies. We value curiosity and resourcefulness alongside technical skill.

There is room to grow from running and adapting existing processes toward owning pipelines and contributing to downstream analyses.

KEY RESPONSIBILITIES

Curate, clean, and harmonize multi-omic, survey, biochemistry, and clinical data from international field sites and partner cohorts, reconciling differences across studies, platforms, and sites. Build reproducible QC (validation checks and anomaly detection) that flags problematic data; drive solutions to trace root causes and suggests long term solutions. Contribute to study design, sample selection, and randomization schemes for multi-omic data generation.

Catch data issues early and work with the internal team overseeing data collection to resolve them at the source. Run and adapt the ETL/ELT pipelines that ingest field data with room to own them over time. Prepare analysis-ready datasets, analyses, and quality assessments that feed downstream target discovery, with clear documentation throughout.

Support quality data generation through occasional wet lab work including aliquoting, protocol testing, and sample QC.

QUALIFICATIONS

Must Have... MS or PhD in epidemiology, biostatistics, genetics, bioinformatics, data science, public health, computational biology, or a related field - or bachelors with a minimum of 2 years relevant professional experience. Demonstrated experience with large, imperfect real-world datasets (multi-omic, survey, biochemistry, and/or clinical) and a track record of catching quality issues before they reach an analysis and tracing them back to their cause.

Basic proficiency in R, Python, or a similar programming/scripting language. Genomic study-design literacy: Able to recognize when recruitment, sampling, batching, or measurement decisions could introduce bias or confounding, and what the resulting data can and cannot support. Prior wet lab experience in molecular biology or related context.