Associate Scientist, Health Data

Position: (Associate) Scientist, Health Data
# (Associate) Scientist, Health Data Variant Bio Be an Early Applicant Full Time junior Seattle, Washington, US $100k – $150k Posted Today##

Role Overview Variant Bio is hiring a entry-level (Associate) Scientist, Health Data. This is a full-time role in Seattle, Washington. posted today. The posted range is $100k to $150k; applications are still in the early window, before most candidates have applied. Full responsibilities, required qualifications, and the apply link are listed in the description below.## Resume Keywords to Include Make sure these keywords appear in your resume to improve ATS scoring

PythonRSQLAWSGitORCompensation Benefits Sign  up free to auto-tailor your resume with all these keywords and get a higher ATS score## Job description

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.

With ethics at its core, the company launched an unprecedented benefit-sharing program in 2020, in which it has pledged tangible 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 cess 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.

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.
* A learning mindset and creative problem-solving; comfortable working at the edge of your expertise and drawing on a cross-functional team to solve unfamiliar problems.
* Strong attention to detail and record-keeping, and the ability to manage parallel workflows across multiple studies.
* Clear communication and comfort…